Index

A B C D E F G H I J K L M N O P Q R S T U V W X Z

A

aat() - Method in class smile.math.matrix.BandMatrix
aat() - Method in interface smile.math.matrix.DenseMatrix
aat() - Method in class smile.math.matrix.JMatrix
aat() - Method in interface smile.math.matrix.Matrix: Returns A * A'
aat() - Method in class smile.math.matrix.SparseMatrix
abmm(DenseMatrix) - Method in class smile.math.matrix.JMatrix
abmm(B) - Method in interface smile.math.matrix.MatrixMultiplication: Returns the result of matrix multiplication A * B.
abmm(SparseMatrix) - Method in class smile.math.matrix.SparseMatrix: Returns the matrix multiplication C = A * B.
abs() - Method in class smile.math.Complex: Returns abs/modulus/magnitude.
AbstractDifferentiableMultivariateFunction - Class in smile.math: An abstract implementation that uses finite differences to calculate the partial derivatives instead of providing them analytically.
AbstractDifferentiableMultivariateFunction() - Constructor for class smile.math.AbstractDifferentiableMultivariateFunction
AbstractDistribution - Class in smile.stat.distribution: The base class of univariate distributions.
AbstractDistribution() - Constructor for class smile.stat.distribution.AbstractDistribution
abtmm(DenseMatrix) - Method in class smile.math.matrix.JMatrix
abtmm(B) - Method in interface smile.math.matrix.MatrixMultiplication: Returns the result of matrix multiplication A * B'.
abtmm(SparseMatrix) - Method in class smile.math.matrix.SparseMatrix
accept(int, int, double) - Method in interface smile.math.matrix.MatrixElementConsumer
add(String, T) - Method in class smile.hash.PerfectMap.Builder: Add a new key-value pair.
add(Complex) - Method in class smile.math.Complex: Returns this + b.
add(double[], double[]) - Static method in class smile.math.MathEx: Element-wise sum of two arrays y = x + y.
add(int, int, double) - Method in interface smile.math.matrix.DenseMatrix: A[i][j] += x
add(DenseMatrix, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: C = A + B
add(DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: In place addition A = A + B
add(double, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: Element-wise addition C = A + x
add(double) - Method in interface smile.math.matrix.DenseMatrix: In place element-wise addition A = A + x
add(int, int, double) - Method in class smile.math.matrix.JMatrix
add(DenseMatrix) - Method in class smile.math.matrix.JMatrix
add(JMatrix) - Method in class smile.math.matrix.JMatrix
add(DenseMatrix, DenseMatrix) - Method in class smile.math.matrix.JMatrix
add(JMatrix, JMatrix) - Method in class smile.math.matrix.JMatrix
add(double) - Method in class smile.math.matrix.JMatrix
add(double, DenseMatrix) - Method in class smile.math.matrix.JMatrix
add(double, JMatrix) - Method in class smile.math.matrix.JMatrix
add(double) - Method in class smile.sort.DoubleHeapSelect: Assimilate a new value from the stream.
add(float) - Method in class smile.sort.FloatHeapSelect: Assimilate a new value from the stream.
add(T) - Method in class smile.sort.HeapSelect: Assimilate a new value from the stream.
add(int) - Method in class smile.sort.IntHeapSelect: Assimilate a new value from the stream.
add(double) - Method in class smile.sort.IQAgent: Assimilate a new value from the stream.
add(int, int, double) - Method in class smile.util.Array2D
add(Array2D) - Method in class smile.util.Array2D
add(double) - Method in class smile.util.Array2D
add(double) - Method in class smile.util.DoubleArrayList: Appends the specified value to the end of this list.
add(double[]) - Method in class smile.util.DoubleArrayList: Appends an array to the end of this list.
add(int, int, int) - Method in class smile.util.IntArray2D
add(IntArray2D) - Method in class smile.util.IntArray2D
add(int) - Method in class smile.util.IntArray2D
add(int) - Method in class smile.util.IntArrayList: Appends the specified value to the end of this list.
add(IntArrayList) - Method in class smile.util.IntArrayList: Appends an array to the end of this list.
add(int[]) - Method in class smile.util.IntArrayList: Appends an array to the end of this list.
add(int) - Method in class smile.util.IntHashSet: Adds the specified element to this set if it is not already present.
all(boolean[]) - Static method in class smile.math.MathEx: Given a set of boolean values, are all of the values true?
alpha - Variable in class smile.stat.distribution.BetaDistribution: The shape parameter.
any(boolean[]) - Static method in class smile.math.MathEx: Given a set of boolean values, is at least one of the values true?
append(int, double) - Method in class smile.util.SparseArray: Append an entry to the array, optimizing for the case where the index is greater than all existing indices in the array.
apply(int) - Method in class smile.math.Complex.Array: Returns the i-th element.
apply(T, T) - Method in interface smile.math.distance.Distance: Returns the distance measure between two objects.
apply(double) - Method in interface smile.math.Function: Computes the value of the function at x.
apply(int) - Method in interface smile.math.IntFunction: Computes the value of the function at x.
apply(T, T) - Method in interface smile.math.kernel.MercerKernel: Kernel function.
apply(int, int, int, int) - Method in interface smile.math.matrix.DenseMatrix: Returns the submatrix which top left at (i, j) and bottom right at (k, l).
apply(int, int) - Method in interface smile.math.matrix.Matrix: Returns the entry value at row i and column j.
apply(double...) - Method in interface smile.math.MultivariateFunction: Computes the value of the function at x.
apply(int, int) - Method in class smile.util.Array2D: Returns A(i, j).
apply(int, int) - Method in class smile.util.IntArray2D: Returns A(i, j).
applyAsDouble(T, T) - Method in interface smile.math.distance.Distance
applyAsDouble(T, T) - Method in interface smile.math.kernel.MercerKernel
applyAsDouble(double[]) - Method in interface smile.math.MultivariateFunction
applyAsFloat(T) - Method in interface smile.util.ToFloatFunction: Applies this function to the given argument.
Array(int) - Constructor for class smile.math.Complex.Array: Constructor.
Array2D - Class in smile.util: 2-dimensional array of doubles.
Array2D(double[][]) - Constructor for class smile.util.Array2D: Constructor.
Array2D(int, int) - Constructor for class smile.util.Array2D: Constructor of all-zero matrix.
Array2D(int, int, double) - Constructor for class smile.util.Array2D: Constructor.
Array2D(int, int, double[]) - Constructor for class smile.util.Array2D: Constructor.
ata() - Method in class smile.math.matrix.BandMatrix
ata() - Method in interface smile.math.matrix.DenseMatrix
ata() - Method in class smile.math.matrix.JMatrix
ata() - Method in interface smile.math.matrix.Matrix: Returns A' * A
ata() - Method in class smile.math.matrix.SparseMatrix
atbmm(DenseMatrix) - Method in class smile.math.matrix.JMatrix
atbmm(B) - Method in interface smile.math.matrix.MatrixMultiplication: Returns the result of matrix multiplication A' * B.
atbmm(SparseMatrix) - Method in class smile.math.matrix.SparseMatrix
atbtmm(DenseMatrix) - Method in class smile.math.matrix.JMatrix
atbtmm(B) - Method in interface smile.math.matrix.MatrixMultiplication: Returns the result of matrix multiplication A' * B'.
atbtmm(SparseMatrix) - Method in class smile.math.matrix.SparseMatrix
atx(double[], double[]) - Method in class smile.math.matrix.BandMatrix
atx(double[], double[]) - Method in class smile.math.matrix.JMatrix
atx(double[], double[]) - Method in interface smile.math.matrix.Matrix: y = A' * x
atx(double[], double[]) - Method in class smile.math.matrix.SparseMatrix
atxpy(double[], double[]) - Method in class smile.math.matrix.BandMatrix
atxpy(double[], double[], double) - Method in class smile.math.matrix.BandMatrix
atxpy(double[], double[]) - Method in class smile.math.matrix.JMatrix
atxpy(double[], double[], double) - Method in class smile.math.matrix.JMatrix
atxpy(double[], double[]) - Method in interface smile.math.matrix.Matrix: y = A' * x + y
atxpy(double[], double[], double) - Method in interface smile.math.matrix.Matrix: y = A' * x + b * y
atxpy(double[], double[]) - Method in class smile.math.matrix.SparseMatrix
atxpy(double[], double[], double) - Method in class smile.math.matrix.SparseMatrix
ax(double[], double[]) - Method in class smile.math.matrix.BandMatrix
ax(double[], double[]) - Method in class smile.math.matrix.JMatrix
ax(double[], double[]) - Method in interface smile.math.matrix.Matrix: y = A * x
ax(double[], double[]) - Method in class smile.math.matrix.SparseMatrix
axpy(double, double[], double[]) - Static method in class smile.math.MathEx: Update an array by adding a multiple of another array y = a * x + y.
axpy(double[], double[]) - Method in class smile.math.matrix.BandMatrix
axpy(double[], double[], double) - Method in class smile.math.matrix.BandMatrix
axpy(double[], double[]) - Method in class smile.math.matrix.JMatrix
axpy(double[], double[], double) - Method in class smile.math.matrix.JMatrix
axpy(double[], double[]) - Method in interface smile.math.matrix.Matrix: y = A * x + y
axpy(double[], double[], double) - Method in interface smile.math.matrix.Matrix: y = A * x + b * y
axpy(double[], double[]) - Method in class smile.math.matrix.SparseMatrix
axpy(double[], double[], double) - Method in class smile.math.matrix.SparseMatrix

B

BandMatrix - Class in smile.math.matrix: A band matrix is a sparse matrix, whose non-zero entries are confined to a diagonal band, comprising the main diagonal and zero or more diagonals on either side.
BandMatrix(int, int) - Constructor for class smile.math.matrix.BandMatrix: Constructor of an n-by-n band-diagonal matrix A with m subdiagonal rows and m superdiagonal rows.
BandMatrix(int, int, int) - Constructor for class smile.math.matrix.BandMatrix: Constructor of an n-by-n band-diagonal matrix A with m₁ subdiagonal rows and m₂ superdiagonal rows.
bandwidth() - Method in class smile.stat.distribution.KernelDensity: Returns the bandwidth of kernel.
BernoulliDistribution - Class in smile.stat.distribution: Bernoulli distribution is a discrete probability distribution, which takes value 1 with success probability p and value 0 with failure probability q = 1 - p.
BernoulliDistribution(double) - Constructor for class smile.stat.distribution.BernoulliDistribution: Constructor.
BernoulliDistribution(boolean[]) - Constructor for class smile.stat.distribution.BernoulliDistribution: Construct an Bernoulli from the given samples.
Beta - Class in smile.math.special: The beta function, also called the Euler integral of the first kind.
beta(double, double) - Static method in class smile.math.special.Beta: Beta function, also called the Euler integral of the first kind.
beta - Variable in class smile.stat.distribution.BetaDistribution: The shape parameter.
BetaDistribution - Class in smile.stat.distribution: The beta distribution is defined on the interval [0, 1] parameterized by two positive shape parameters, typically denoted by α and β.
BetaDistribution(double, double) - Constructor for class smile.stat.distribution.BetaDistribution: Constructor.
BFGS - Class in smile.math: The Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm is an iterative method for solving unconstrained nonlinear optimization problems.
BFGS() - Constructor for class smile.math.BFGS: Constructor with gtol = 1E-5 and maxIter = 500.
BFGS(double, int) - Constructor for class smile.math.BFGS: Constructor.
BFGS - Static variable in class smile.math.MathEx: The Broyden–Fletcher–Goldfarb–Shanno (BFGS) algorithm for unconstrained nonlinear optimization problems.
bic - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture: The BIC score when the distribution is fit on a sample data.
bic(double[]) - Method in class smile.stat.distribution.DiscreteMixture: BIC score of the mixture for given data.
bic - Variable in class smile.stat.distribution.ExponentialFamilyMixture: The BIC score when the distribution is fit on a sample data.
bic(double[]) - Method in class smile.stat.distribution.Mixture: The BIC score of the mixture for given data.
bic - Variable in class smile.stat.distribution.MultivariateExponentialFamilyMixture: The BIC score when the distribution is fit on a sample data.
bic(double[][]) - Method in class smile.stat.distribution.MultivariateMixture: BIC score of the mixture for given data.
bic(double, int, int) - Static method in class smile.stat.Stat: Bayesian information criterion (BIC).
BiconjugateGradient - Class in smile.math.matrix: The biconjugate gradient method is an algorithm to solve systems of linear equations.
BiconjugateGradient() - Constructor for class smile.math.matrix.BiconjugateGradient: Constructor with itol = 1 and tol = 1E-10.
BiconjugateGradient(double, int, int) - Constructor for class smile.math.matrix.BiconjugateGradient: Constructor.
BinarySparseGaussianKernel - Class in smile.math.kernel: The Gaussian Mercer Kernel.
BinarySparseGaussianKernel(double) - Constructor for class smile.math.kernel.BinarySparseGaussianKernel: Constructor.
BinarySparseHyperbolicTangentKernel - Class in smile.math.kernel: The hyperbolic tangent kernel.
BinarySparseHyperbolicTangentKernel() - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel: Constructor with scale 1.0 and offset 0.0.
BinarySparseHyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.BinarySparseHyperbolicTangentKernel: Constructor.
BinarySparseLaplacianKernel - Class in smile.math.kernel: The Laplacian Kernel.
BinarySparseLaplacianKernel(double) - Constructor for class smile.math.kernel.BinarySparseLaplacianKernel: Constructor.
BinarySparseLinearKernel - Class in smile.math.kernel: The linear dot product kernel on sparse binary arrays in int[], which are the indices of nonzero elements.
BinarySparseLinearKernel() - Constructor for class smile.math.kernel.BinarySparseLinearKernel: Constructor.
BinarySparsePolynomialKernel - Class in smile.math.kernel: The polynomial kernel.
BinarySparsePolynomialKernel(int) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel: Constructor with scale 1 and bias 0.
BinarySparsePolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.BinarySparsePolynomialKernel: Constructor.
BinarySparseThinPlateSplineKernel - Class in smile.math.kernel: The Thin Plate Spline Kernel.
BinarySparseThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.BinarySparseThinPlateSplineKernel: Constructor.
BinomialDistribution - Class in smile.stat.distribution: The binomial distribution is the discrete probability distribution of the number of successes in a sequence of n independent yes/no experiments, each of which yields success with probability p.
BinomialDistribution(int, double) - Constructor for class smile.stat.distribution.BinomialDistribution: Constructor.
bins(double[], double) - Static method in interface smile.math.Histogram: Returns the number of bins for a data based on a suggested bin width h.
bins(int) - Static method in interface smile.math.Histogram: Returns the number of bins by square-root rule, which takes the square root of the number of data points in the sample (used by Excel histograms and many others).
breaks(double[], double) - Static method in interface smile.math.Histogram: Returns the breakpoints between histogram cells for a dataset based on a suggested bin width h.
breaks(double, double, double) - Static method in interface smile.math.Histogram: Returns the breakpoints between histogram cells for a given range based on a suggested bin width h.
breaks(double[], int) - Static method in interface smile.math.Histogram: Returns the breakpoints between histogram cells for a dataset.
breaks(double, double, int) - Static method in interface smile.math.Histogram: Returns the breakpoints between histogram cells for a given range.
build() - Method in class smile.hash.PerfectMap.Builder: Builds the perfect map.
Builder() - Constructor for class smile.hash.PerfectMap.Builder: Constructor.
Builder(Map<String, T>) - Constructor for class smile.hash.PerfectMap.Builder: Constructor.

C

c(int...) - Static method in class smile.math.MathEx: Combines the arguments to form a vector.
c(float...) - Static method in class smile.math.MathEx: Combines the arguments to form a vector.
c(double...) - Static method in class smile.math.MathEx: Combines the arguments to form a vector.
c(String...) - Static method in class smile.math.MathEx: Combines the arguments to form a vector.
c(int[]...) - Static method in class smile.math.MathEx: Merges multiple vectors into one.
c(float[]...) - Static method in class smile.math.MathEx: Merges multiple vectors into one.
c(double[]...) - Static method in class smile.math.MathEx: Merges multiple vectors into one.
c(String[]...) - Static method in class smile.math.MathEx: Concatenates multiple vectors into one array of strings.
cbind(int[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by columns.
cbind(float[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by columns.
cbind(double[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by columns.
cbind(String[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by columns.
cdf(double) - Method in class smile.stat.distribution.BernoulliDistribution
cdf(double) - Method in class smile.stat.distribution.BetaDistribution
cdf(double) - Method in class smile.stat.distribution.BinomialDistribution
cdf(double) - Method in class smile.stat.distribution.ChiSquareDistribution
cdf(double) - Method in class smile.stat.distribution.DiscreteMixture
cdf(double) - Method in interface smile.stat.distribution.Distribution: Cumulative distribution function.
cdf(double) - Method in class smile.stat.distribution.EmpiricalDistribution
cdf(double) - Method in class smile.stat.distribution.ExponentialDistribution
cdf(double) - Method in class smile.stat.distribution.FDistribution
cdf(double) - Method in class smile.stat.distribution.GammaDistribution
cdf(double) - Method in class smile.stat.distribution.GaussianDistribution
cdf(double) - Method in class smile.stat.distribution.GeometricDistribution
cdf(double) - Method in class smile.stat.distribution.HyperGeometricDistribution
cdf(double) - Method in class smile.stat.distribution.KernelDensity: Cumulative distribution function.
cdf(double) - Method in class smile.stat.distribution.LogisticDistribution
cdf(double) - Method in class smile.stat.distribution.LogNormalDistribution
cdf(double) - Method in class smile.stat.distribution.Mixture
cdf(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution: Cumulative distribution function.
cdf(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution: Algorithm from Alan Genz (1992) Numerical Computation of Multivariate Normal Probabilities, Journal of Computational and Graphical Statistics, pp.
cdf(double[]) - Method in class smile.stat.distribution.MultivariateMixture
cdf(double) - Method in class smile.stat.distribution.NegativeBinomialDistribution
cdf(double) - Method in class smile.stat.distribution.PoissonDistribution
cdf(double) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
cdf(double) - Method in class smile.stat.distribution.TDistribution
cdf(double) - Method in class smile.stat.distribution.WeibullDistribution
cdf2tiled(double) - Method in class smile.stat.distribution.TDistribution: Two-tailed cdf.
change(int) - Method in class smile.util.PriorityQueue: The priority of item k has changed.
ChebyshevDistance - Class in smile.math.distance: Chebyshev distance (or Tchebychev distance), or L_∞ metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.
ChebyshevDistance() - Constructor for class smile.math.distance.ChebyshevDistance: Constructor.
chisq - Variable in class smile.stat.hypothesis.ChiSqTest: chi-square statistic
ChiSqTest - Class in smile.stat.hypothesis: Pearson's chi-square test, also known as the chi-square goodness-of-fit test or chi-square test for independence.
ChiSquareDistribution - Class in smile.stat.distribution: Chi-square (or chi-squared) distribution with k degrees of freedom is the distribution of a sum of the squares of k independent standard normal random variables.
ChiSquareDistribution(int) - Constructor for class smile.stat.distribution.ChiSquareDistribution: Constructor.
Cholesky - Class in smile.math.matrix: Cholesky decomposition is a decomposition of a symmetric, positive-definite matrix into a lower triangular matrix L and the transpose of the lower triangular matrix such that A = L*L'.
Cholesky(DenseMatrix) - Constructor for class smile.math.matrix.Cholesky: Constructor.
cholesky() - Method in interface smile.math.matrix.DenseMatrix: Returns the Cholesky decomposition.
cholesky(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the Cholesky decomposition.
cholesky() - Method in class smile.math.matrix.JMatrix: Cholesky decomposition for symmetric and positive definite matrix.
CholeskyOfAtA() - Method in class smile.math.matrix.QR: Returns the Cholesky decomposition of A'A.
choose(int, int) - Static method in class smile.math.MathEx: The n choose k.
clear() - Method in class smile.util.DoubleArrayList: Removes all of the values from this list.
clear() - Method in class smile.util.IntArrayList: Removes all of the value from this list.
clone(int[][]) - Static method in class smile.math.MathEx: Deep clone a two-dimensional array.
clone(float[][]) - Static method in class smile.math.MathEx: Deep clone a two-dimensional array.
clone(double[][]) - Static method in class smile.math.MathEx: Deep clone a two-dimensional array.
colMax(int[][]) - Static method in class smile.math.MathEx: Returns the column maximum for a matrix.
colMax(double[][]) - Static method in class smile.math.MathEx: Returns the column maximum for a matrix.
colMeans(double[][]) - Static method in class smile.math.MathEx: Returns the column means for a matrix.
colMeans() - Method in interface smile.math.matrix.DenseMatrix: Returns the mean of each column.
colMin(int[][]) - Static method in class smile.math.MathEx: Returns the column minimum for a matrix.
colMin(double[][]) - Static method in class smile.math.MathEx: Returns the column minimum for a matrix.
colSds(double[][]) - Static method in class smile.math.MathEx: Returns the column deviations for a matrix.
colSds() - Method in interface smile.math.matrix.DenseMatrix: Returns the standard deviations of each column.
colSums(int[][]) - Static method in class smile.math.MathEx: Returns the column sums for a matrix.
colSums(double[][]) - Static method in class smile.math.MathEx: Returns the column sums for a matrix.
colSums() - Method in interface smile.math.matrix.DenseMatrix: Returns the sum of each column.
Complex - Class in smile.math: Complex number.
Complex(double, double) - Constructor for class smile.math.Complex: Constructor.
Complex.Array - Class in smile.math: Packed array of complex numbers for better memory efficiency.
Component(double, DiscreteDistribution) - Constructor for class smile.stat.distribution.DiscreteMixture.Component: Constructor.
Component(double, Distribution) - Constructor for class smile.stat.distribution.Mixture.Component: Constructor.
Component(double, MultivariateDistribution) - Constructor for class smile.stat.distribution.MultivariateMixture.Component: Constructor.
components - Variable in class smile.stat.distribution.DiscreteMixture: The components of finite mixture model.
components - Variable in class smile.stat.distribution.Mixture: The components of finite mixture model.
components - Variable in class smile.stat.distribution.MultivariateMixture: The components of finite mixture model.
condition() - Method in class smile.math.matrix.SVD: Returns the L₂ norm condition number, which is max(S) / min(S).
conjugate() - Method in class smile.math.Complex: Returns the conjugate.
constant(double) - Static method in interface smile.math.TimeFunction: Returns the constant learning rate.
contains(double[][], double[]) - Static method in class smile.math.MathEx: Determines if the polygon contains the specified coordinates.
contains(double[][], double, double) - Static method in class smile.math.MathEx: Determines if the polygon contains the specified coordinates.
contains(int) - Method in class smile.util.IntHashSet: Returns true if this set contains the specified element.
copy(int[], int[]) - Static method in class smile.math.MathEx: Copy x into y.
copy(float[], float[]) - Static method in class smile.math.MathEx: Copy x into y.
copy(double[], double[]) - Static method in class smile.math.MathEx: Copy x into y.
copy(int[][], int[][]) - Static method in class smile.math.MathEx: Copy x into y.
copy(float[][], float[][]) - Static method in class smile.math.MathEx: Copy x into y.
copy(double[][], double[][]) - Static method in class smile.math.MathEx: Copy x into y.
copy() - Method in interface smile.math.matrix.DenseMatrix: Returns a copy of this matrix.
copy() - Method in class smile.math.matrix.JMatrix
cor(int[], int[]) - Static method in class smile.math.MathEx: Returns the correlation coefficient between two vectors.
cor(float[], float[]) - Static method in class smile.math.MathEx: Returns the correlation coefficient between two vectors.
cor(double[], double[]) - Static method in class smile.math.MathEx: Returns the correlation coefficient between two vectors.
cor(double[][]) - Static method in class smile.math.MathEx: Returns the sample correlation matrix.
cor(double[][], double[]) - Static method in class smile.math.MathEx: Returns the sample correlation matrix.
cor - Variable in class smile.stat.hypothesis.CorTest: Correlation coefficient
CorrelationDistance - Class in smile.math.distance: Correlation distance is defined as 1 - correlation coefficient.
CorrelationDistance() - Constructor for class smile.math.distance.CorrelationDistance: Constructor of Pearson correlation distance.
CorrelationDistance(String) - Constructor for class smile.math.distance.CorrelationDistance: Constructor.
CorTest - Class in smile.stat.hypothesis: Correlation test.
cos() - Method in class smile.math.Complex: Returns the complex cosine.
cov(int[], int[]) - Static method in class smile.math.MathEx: Returns the covariance between two vectors.
cov(float[], float[]) - Static method in class smile.math.MathEx: Returns the covariance between two vectors.
cov(double[], double[]) - Static method in class smile.math.MathEx: Returns the covariance between two vectors.
cov(double[][]) - Static method in class smile.math.MathEx: Returns the sample covariance matrix.
cov(double[][], double[]) - Static method in class smile.math.MathEx: Returns the sample covariance matrix.
cov() - Method in interface smile.stat.distribution.MultivariateDistribution: The covariance matrix of distribution.
cov() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
cov() - Method in class smile.stat.distribution.MultivariateMixture

D

d(int[], int[]) - Static method in class smile.math.distance.ChebyshevDistance: Chebyshev distance between the two arrays of type integer.
d(float[], float[]) - Static method in class smile.math.distance.ChebyshevDistance: Chebyshev distance between the two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.ChebyshevDistance: Chebyshev distance between the two arrays of type double.
d(double[], double[]) - Method in class smile.math.distance.CorrelationDistance: Pearson correlation distance between the two arrays of type double.
d(T, T) - Method in interface smile.math.distance.Distance: Returns the distance measure between two objects.
d(T[], T[]) - Method in class smile.math.distance.DynamicTimeWarping
d(int[], int[]) - Static method in class smile.math.distance.DynamicTimeWarping: Dynamic time warping without path constraints.
d(int[], int[], int) - Static method in class smile.math.distance.DynamicTimeWarping: Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.
d(float[], float[]) - Static method in class smile.math.distance.DynamicTimeWarping: Dynamic time warping without path constraints.
d(float[], float[], int) - Static method in class smile.math.distance.DynamicTimeWarping: Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.
d(double[], double[]) - Static method in class smile.math.distance.DynamicTimeWarping: Dynamic time warping without path constraints.
d(double[], double[], int) - Static method in class smile.math.distance.DynamicTimeWarping: Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.
d(String, String) - Method in class smile.math.distance.EditDistance: Edit distance between two strings.
d(char[], char[]) - Method in class smile.math.distance.EditDistance: Edit distance between two strings.
d(int[], int[]) - Method in class smile.math.distance.EuclideanDistance: Euclidean distance between the two arrays of type integer.
d(float[], float[]) - Method in class smile.math.distance.EuclideanDistance: Euclidean distance between the two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.EuclideanDistance: Euclidean distance between the two arrays of type double.
d(BitSet, BitSet) - Method in class smile.math.distance.HammingDistance
d(byte, byte) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two bytes.
d(short, short) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two shorts.
d(int, int) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two integers.
d(long, long) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two long integers.
d(byte[], byte[]) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two byte arrays.
d(short[], short[]) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two short arrays.
d(int[], int[]) - Static method in class smile.math.distance.HammingDistance: Returns Hamming distance between the two integer arrays.
d(T[], T[]) - Method in class smile.math.distance.JaccardDistance
d(Set<T>, Set<T>) - Static method in class smile.math.distance.JaccardDistance: Returns the Jaccard distance between sets.
d(double[], double[]) - Method in class smile.math.distance.JensenShannonDistance
d(int[], int[]) - Method in class smile.math.distance.LeeDistance
d(double[], double[]) - Method in class smile.math.distance.MahalanobisDistance
d(int[], int[]) - Method in class smile.math.distance.ManhattanDistance: Manhattan distance between two arrays of type integer.
d(float[], float[]) - Method in class smile.math.distance.ManhattanDistance: Manhattan distance between two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.ManhattanDistance: Manhattan distance between two arrays of type double.
d(int[], int[]) - Method in class smile.math.distance.MinkowskiDistance: Minkowski distance between the two arrays of type integer.
d(float[], float[]) - Method in class smile.math.distance.MinkowskiDistance: Minkowski distance between the two arrays of type float.
d(double[], double[]) - Method in class smile.math.distance.MinkowskiDistance: Minkowski distance between the two arrays of type double.
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseChebyshevDistance
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseEuclideanDistance
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseManhattanDistance
d(SparseArray, SparseArray) - Method in class smile.math.distance.SparseMinkowskiDistance
d - Variable in class smile.stat.hypothesis.KSTest: Kolmogorov-Smirnov statistic
damerau(String, String) - Static method in class smile.math.distance.EditDistance: Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.
damerau(char[], char[]) - Static method in class smile.math.distance.EditDistance: Damerau-Levenshtein distance between two strings allows insertion, deletion, substitution, or transposition of characters.
data() - Method in interface smile.math.matrix.DenseMatrix: Returns the array that backs this matrix (optional operation).
data() - Method in class smile.math.matrix.JMatrix
decimal(double) - Static method in interface smile.util.Strings: Returns the decimal string representation of a floating number.
decimalFormat - Static variable in interface smile.util.Strings: Decimal format for floating numbers.
decompose() - Method in class smile.math.matrix.BandMatrix: LU decomposition.
decrement() - Method in class smile.util.MutableInt: Decrement by one.
decrement(int) - Method in class smile.util.MutableInt: Decrement.
DenseMatrix - Interface in smile.math.matrix: An abstract interface of dense matrix.
det() - Method in class smile.math.matrix.BandMatrix: Returns the matrix determinant.
det() - Method in class smile.math.matrix.Cholesky: Returns the matrix determinant
det() - Method in class smile.math.matrix.LU: Returns the matrix determinant
df - Variable in class smile.stat.hypothesis.ChiSqTest: The degree of freedom of chisq-statistic.
df - Variable in class smile.stat.hypothesis.CorTest: Degree of freedom
df - Variable in class smile.stat.hypothesis.TTest: The degree of freedom of t-statistic.
df1 - Variable in class smile.stat.hypothesis.FTest: The degree of freedom of f-statistic.
df2 - Variable in class smile.stat.hypothesis.FTest: The degree of freedom of f-statistic.
diag() - Method in class smile.math.matrix.BandMatrix
diag(double[]) - Static method in interface smile.math.matrix.Matrix: Returns a square diagonal matrix with the elements of vector diag on the main diagonal.
diag() - Method in interface smile.math.matrix.Matrix: Returns the diagonal elements.
diag() - Method in class smile.math.matrix.SparseMatrix
diagonal - Variable in class smile.stat.distribution.MultivariateGaussianDistribution: True if the covariance matrix is diagonal.
DifferentiableFunction - Interface in smile.math: A differentiable function is a function whose derivative exists at each point in its domain.
DifferentiableMultivariateFunction - Interface in smile.math: A differentiable function is a function whose derivative exists at each point in its domain.
digamma(double) - Static method in class smile.math.special.Gamma: The digamma function is defined as the logarithmic derivative of the gamma function.
DIGITS - Static variable in class smile.math.MathEx: The number of digits (in radix base) in the mantissa.
DiscreteDistribution - Class in smile.stat.distribution: This is the base class of univariate discrete distributions.
DiscreteDistribution() - Constructor for class smile.stat.distribution.DiscreteDistribution
DiscreteExponentialFamily - Interface in smile.stat.distribution: The purpose of this interface is mainly to define the method M that is the Maximization step in the EM algorithm.
DiscreteExponentialFamilyMixture - Class in smile.stat.distribution: The finite mixture of distributions from discrete exponential family.
DiscreteExponentialFamilyMixture(DiscreteMixture.Component...) - Constructor for class smile.stat.distribution.DiscreteExponentialFamilyMixture: Constructor.
DiscreteMixture - Class in smile.stat.distribution: The finite mixture of discrete distributions.
DiscreteMixture(DiscreteMixture.Component...) - Constructor for class smile.stat.distribution.DiscreteMixture: Constructor.
DiscreteMixture.Component - Class in smile.stat.distribution: A component in the mixture distribution is defined by a distribution and its weight in the mixture.
Distance<T> - Interface in smile.math.distance: An interface to calculate a distance measure between two objects.
distance(int[], int[]) - Static method in class smile.math.MathEx: The Euclidean distance.
distance(float[], float[]) - Static method in class smile.math.MathEx: The Euclidean distance.
distance(double[], double[]) - Static method in class smile.math.MathEx: The Euclidean distance.
distance(SparseArray, SparseArray) - Static method in class smile.math.MathEx: The Euclidean distance.
distribution - Variable in class smile.stat.distribution.DiscreteMixture.Component: The distribution of component.
Distribution - Interface in smile.stat.distribution: Probability distribution of univariate random variable.
distribution - Variable in class smile.stat.distribution.Mixture.Component: The distribution of component.
distribution - Variable in class smile.stat.distribution.MultivariateMixture.Component: The distribution of component.
div(Complex) - Method in class smile.math.Complex: Returns a / b.
div(int, int, double) - Method in interface smile.math.matrix.DenseMatrix: A[i][j] /= x
div(DenseMatrix, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: C = A / B
div(DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: In place element-wise division A = A / B A = A - B
div(double, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: Element-wise addition C = A / x
div(double) - Method in interface smile.math.matrix.DenseMatrix: In place element-wise division A = A / x
div(int, int, double) - Method in class smile.math.matrix.JMatrix
div(DenseMatrix) - Method in class smile.math.matrix.JMatrix
div(JMatrix) - Method in class smile.math.matrix.JMatrix
div(DenseMatrix, DenseMatrix) - Method in class smile.math.matrix.JMatrix
div(JMatrix, JMatrix) - Method in class smile.math.matrix.JMatrix
div(double) - Method in class smile.math.matrix.JMatrix
div(double, DenseMatrix) - Method in class smile.math.matrix.JMatrix
div(double, JMatrix) - Method in class smile.math.matrix.JMatrix
div(int, int, double) - Method in class smile.util.Array2D
div(Array2D) - Method in class smile.util.Array2D
div(double) - Method in class smile.util.Array2D
div(int, int, int) - Method in class smile.util.IntArray2D
div(IntArray2D) - Method in class smile.util.IntArray2D
div(int) - Method in class smile.util.IntArray2D
dot(int[], int[]) - Static method in class smile.math.MathEx: Returns the dot product between two vectors.
dot(float[], float[]) - Static method in class smile.math.MathEx: Returns the dot product between two vectors.
dot(double[], double[]) - Static method in class smile.math.MathEx: Returns the dot product between two vectors.
dot(SparseArray, SparseArray) - Static method in class smile.math.MathEx: Returns the dot product between two sparse arrays.
DoubleArrayList - Class in smile.util: A resizeable, array-backed list of double primitives.
DoubleArrayList() - Constructor for class smile.util.DoubleArrayList: Constructs an empty list.
DoubleArrayList(int) - Constructor for class smile.util.DoubleArrayList: Constructs an empty list with the specified initial capacity.
DoubleArrayList(double[]) - Constructor for class smile.util.DoubleArrayList: Constructs a list containing the values of the specified array.
DoubleHeapSelect - Class in smile.sort: This class tracks the smallest values seen thus far in a stream of values.
DoubleHeapSelect(int) - Constructor for class smile.sort.DoubleHeapSelect: Constructor.
DoubleHeapSelect(double[]) - Constructor for class smile.sort.DoubleHeapSelect: Constructor.
DynamicTimeWarping<T> - Class in smile.math.distance: Dynamic time warping is an algorithm for measuring similarity between two sequences which may vary in time or speed.
DynamicTimeWarping(Distance<T>) - Constructor for class smile.math.distance.DynamicTimeWarping: Constructor.
DynamicTimeWarping(Distance<T>, double) - Constructor for class smile.math.distance.DynamicTimeWarping: Dynamic time warping with Sakoe-Chiba band, which primarily to prevent unreasonable warping and also improve computational cost.

E

EditDistance - Class in smile.math.distance: The Edit distance between two strings is a metric for measuring the amount of difference between two sequences.
EditDistance() - Constructor for class smile.math.distance.EditDistance: Constructor.
EditDistance(boolean) - Constructor for class smile.math.distance.EditDistance: Constructor.
EditDistance(int) - Constructor for class smile.math.distance.EditDistance: Constructor.
EditDistance(int, boolean) - Constructor for class smile.math.distance.EditDistance: Constructor.
EditDistance(int[][]) - Constructor for class smile.math.distance.EditDistance: Constructor.
EditDistance(int[][], double) - Constructor for class smile.math.distance.EditDistance: Constructor.
eig() - Method in interface smile.math.matrix.DenseMatrix: Returns the eigen values in an array of size 2N.
eig(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the eigen values in an array of size 2N.
eig() - Method in class smile.math.matrix.JMatrix
eigen() - Method in interface smile.math.matrix.DenseMatrix: Returns the eigen value decomposition.
eigen(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the eigen value decomposition.
eigen() - Method in class smile.math.matrix.JMatrix
eigen(Matrix, int) - Static method in class smile.math.matrix.Lanczos: Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(Matrix, int, double, int) - Static method in class smile.math.matrix.Lanczos: Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(int) - Method in interface smile.math.matrix.Matrix: Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(int, double, int) - Method in interface smile.math.matrix.Matrix: Find k largest approximate eigen pairs of a symmetric matrix by the Lanczos algorithm.
eigen(Matrix, double[]) - Static method in class smile.math.matrix.PowerIteration: Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(Matrix, double[], double) - Static method in class smile.math.matrix.PowerIteration: Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(Matrix, double[], double, int) - Static method in class smile.math.matrix.PowerIteration: Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(Matrix, double[], double, double) - Static method in class smile.math.matrix.PowerIteration: Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
eigen(Matrix, double[], double, double, int) - Static method in class smile.math.matrix.PowerIteration: Returns the largest eigen pair of matrix with the power iteration under the assumptions A has an eigenvalue that is strictly greater in magnitude than its other eigenvalues and the starting vector has a nonzero component in the direction of an eigenvector associated with the dominant eigenvalue.
EmpiricalDistribution - Class in smile.stat.distribution: An empirical distribution function or empirical cdf, is a cumulative probability distribution function that concentrates probability 1/n at each of the n numbers in a sample.
EmpiricalDistribution(double[]) - Constructor for class smile.stat.distribution.EmpiricalDistribution: Constructor.
EmpiricalDistribution(double[], IntSet) - Constructor for class smile.stat.distribution.EmpiricalDistribution: Constructor.
empty() - Method in class smile.util.PriorityQueue: Returns true if the queue is empty.
ensureCapacity(int) - Method in class smile.util.DoubleArrayList: Increases the capacity, if necessary, to ensure that it can hold at least the number of values specified by the minimum capacity argument.
ensureCapacity(int) - Method in class smile.util.IntArrayList: Increases the capacity, if necessary, to ensure that it can hold at least the number of values specified by the minimum capacity argument.
entropy(double[]) - Static method in class smile.math.MathEx: Shannon's entropy.
entropy() - Method in class smile.stat.distribution.BernoulliDistribution
entropy() - Method in class smile.stat.distribution.BetaDistribution
entropy() - Method in class smile.stat.distribution.BinomialDistribution
entropy() - Method in class smile.stat.distribution.ChiSquareDistribution
entropy() - Method in class smile.stat.distribution.DiscreteMixture: Shannon entropy.
entropy() - Method in interface smile.stat.distribution.Distribution: Shannon entropy of the distribution.
entropy() - Method in class smile.stat.distribution.EmpiricalDistribution
entropy() - Method in class smile.stat.distribution.ExponentialDistribution
entropy() - Method in class smile.stat.distribution.FDistribution: Shannon entropy.
entropy() - Method in class smile.stat.distribution.GammaDistribution
entropy() - Method in class smile.stat.distribution.GaussianDistribution
entropy() - Method in class smile.stat.distribution.GeometricDistribution: Shannon entropy.
entropy() - Method in class smile.stat.distribution.HyperGeometricDistribution
entropy() - Method in class smile.stat.distribution.KernelDensity: Shannon entropy.
entropy() - Method in class smile.stat.distribution.LogisticDistribution
entropy() - Method in class smile.stat.distribution.LogNormalDistribution
entropy() - Method in class smile.stat.distribution.Mixture: Shannon entropy.
entropy() - Method in interface smile.stat.distribution.MultivariateDistribution: Shannon entropy of the distribution.
entropy() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
entropy() - Method in class smile.stat.distribution.MultivariateMixture: Shannon entropy.
entropy() - Method in class smile.stat.distribution.NegativeBinomialDistribution: Shannon entropy.
entropy() - Method in class smile.stat.distribution.PoissonDistribution
entropy() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
entropy() - Method in class smile.stat.distribution.TDistribution
entropy() - Method in class smile.stat.distribution.WeibullDistribution
EPSILON - Static variable in class smile.math.MathEx: The machine precision for the double type, which is the difference between 1 and the smallest value greater than 1 that is representable for the double type.
equals(Object) - Method in class smile.math.Complex
equals(double, double) - Static method in class smile.math.MathEx: Returns true if two double values equals to each other in the system precision.
equals(float[], float[]) - Static method in class smile.math.MathEx: Check if x element-wisely equals y with default epsilon 1E-7.
equals(float[], float[], float) - Static method in class smile.math.MathEx: Check if x element-wisely equals y.
equals(double[], double[]) - Static method in class smile.math.MathEx: Check if x element-wisely equals y with default epsilon 1E-10.
equals(double[], double[], double) - Static method in class smile.math.MathEx: Check if x element-wisely equals y.
equals(float[][], float[][]) - Static method in class smile.math.MathEx: Check if x element-wisely equals y with default epsilon 1E-7.
equals(float[][], float[][], float) - Static method in class smile.math.MathEx: Check if x element-wisely equals y.
equals(double[][], double[][]) - Static method in class smile.math.MathEx: Check if x element-wisely equals y with default epsilon 1E-10.
equals(double[][], double[][], double) - Static method in class smile.math.MathEx: Check if x element-wisely equals y.
Erf - Class in smile.math.special: The error function (also called the Gauss error function) is a special function of sigmoid shape which occurs in probability, statistics, materials science, and partial differential equations.
erf(double) - Static method in class smile.math.special.Erf: The Gauss error function.
erfc(double) - Static method in class smile.math.special.Erf: The complementary error function.
erfcc(double) - Static method in class smile.math.special.Erf: The complementary error function with fractional error everywhere less than 1.2 × 10^-7.
EuclideanDistance - Class in smile.math.distance: Euclidean distance.
EuclideanDistance() - Constructor for class smile.math.distance.EuclideanDistance: Constructor.
EuclideanDistance(double[]) - Constructor for class smile.math.distance.EuclideanDistance: Constructor with a given weight vector.
EVD - Class in smile.math.matrix: Eigen decomposition of a real matrix.
EVD(DenseMatrix, double[]) - Constructor for class smile.math.matrix.EVD: Private constructor.
EVD(DenseMatrix, double[], double[]) - Constructor for class smile.math.matrix.EVD: Private constructor.
exp() - Method in class smile.math.Complex: Returns the complex exponential.
exp(double, double) - Static method in interface smile.math.TimeFunction: Returns the power series learning rate lambda (alpha * exp(-t/C)).
ExponentialDistribution - Class in smile.stat.distribution: An exponential distribution describes the times between events in a Poisson process, in which events occur continuously and independently at a constant average rate.
ExponentialDistribution(double) - Constructor for class smile.stat.distribution.ExponentialDistribution: Constructor.
ExponentialFamily - Interface in smile.stat.distribution: The exponential family is a class of probability distributions sharing a certain form.
ExponentialFamilyMixture - Class in smile.stat.distribution: The finite mixture of distributions from exponential family.
ExponentialFamilyMixture(Mixture.Component...) - Constructor for class smile.stat.distribution.ExponentialFamilyMixture: Constructor.
eye(int) - Static method in interface smile.math.matrix.Matrix: Returns an n-by-n identity matrix.
eye(int, int) - Static method in interface smile.math.matrix.Matrix: Returns an m-by-n identity matrix.

F

f(double) - Method in interface smile.math.Function: Computes the value of the function at x.
f(int) - Method in interface smile.math.IntFunction: Computes the value of the function at x.
f(double[]) - Method in interface smile.math.MultivariateFunction: Computes the value of the function at x.
f(double) - Method in class smile.math.rbf.GaussianRadialBasis
f(double) - Method in class smile.math.rbf.InverseMultiquadricRadialBasis
f(double) - Method in class smile.math.rbf.MultiquadricRadialBasis
f(double) - Method in class smile.math.rbf.ThinPlateRadialBasis
f - Variable in class smile.stat.hypothesis.FTest: f-statistic
factorial(int) - Static method in class smile.math.MathEx: The factorial of n.
FDistribution - Class in smile.stat.distribution: F-distribution arises in the testing of whether two observed samples have the same variance.
FDistribution(int, int) - Constructor for class smile.stat.distribution.FDistribution: Constructor.
fill(double) - Method in interface smile.math.matrix.DenseMatrix: Fill the matrix with a value.
fill(double) - Method in class smile.math.matrix.JMatrix
fill(char, int) - Static method in interface smile.util.Strings: Returns a string with a single repeated character to a specific length.
find(Function, double, double) - Method in class smile.math.Root: Brent's method for root-finding.
find(DifferentiableFunction, double, double) - Method in class smile.math.Root: Newton's method (also known as the Newton–Raphson method).
fit(int[]) - Static method in class smile.stat.distribution.BernoulliDistribution: Estimates the distribution parameters by MLE.
fit(double[]) - Static method in class smile.stat.distribution.BetaDistribution: Estimates the distribution parameters by the moment method.
fit(int[], DiscreteMixture.Component...) - Static method in class smile.stat.distribution.DiscreteExponentialFamilyMixture: Fits the mixture model with the EM algorithm.
fit(int[], DiscreteMixture.Component[], double, int, double) - Static method in class smile.stat.distribution.DiscreteExponentialFamilyMixture: Fits the mixture model with the EM algorithm.
fit(int[]) - Static method in class smile.stat.distribution.EmpiricalDistribution: Estimates the distribution.
fit(int[], IntSet) - Static method in class smile.stat.distribution.EmpiricalDistribution: Estimates the distribution.
fit(double[]) - Static method in class smile.stat.distribution.ExponentialDistribution: Estimates the distribution parameters by MLE.
fit(double[], Mixture.Component...) - Static method in class smile.stat.distribution.ExponentialFamilyMixture: Fits the mixture model with the EM algorithm.
fit(double[], Mixture.Component[], double, int, double) - Static method in class smile.stat.distribution.ExponentialFamilyMixture: Fits the mixture model with the EM algorithm.
fit(double[]) - Static method in class smile.stat.distribution.GammaDistribution: Estimates the distribution parameters by (approximate) MLE.
fit(double[]) - Static method in class smile.stat.distribution.GaussianDistribution: Estimates the distribution parameters by MLE.
fit(int, double[]) - Static method in class smile.stat.distribution.GaussianMixture: Fits the Gaussian mixture model with the EM algorithm.
fit(double[]) - Static method in class smile.stat.distribution.GaussianMixture: Fits the Gaussian mixture model with the EM algorithm.
fit(int[]) - Static method in class smile.stat.distribution.GeometricDistribution: Estimates the distribution parameters by MLE.
fit(double[]) - Static method in class smile.stat.distribution.LogNormalDistribution: Estimates the distribution parameters by MLE.
fit(double[][], MultivariateMixture.Component...) - Static method in class smile.stat.distribution.MultivariateExponentialFamilyMixture: Fits the mixture model with the EM algorithm.
fit(double[][], MultivariateMixture.Component[], double, int, double) - Static method in class smile.stat.distribution.MultivariateExponentialFamilyMixture: Fits the mixture model with the EM algorithm.
fit(double[][]) - Static method in class smile.stat.distribution.MultivariateGaussianDistribution: Estimates the mean and diagonal covariance by MLE.
fit(double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianDistribution: Estimates the mean and covariance by MLE.
fit(int, double[][]) - Static method in class smile.stat.distribution.MultivariateGaussianMixture: Fits the Gaussian mixture model with the EM algorithm.
fit(int, double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianMixture: Fits the Gaussian mixture model with the EM algorithm.
fit(double[][]) - Static method in class smile.stat.distribution.MultivariateGaussianMixture: Fits the Gaussian mixture model with the EM algorithm.
fit(double[][], boolean) - Static method in class smile.stat.distribution.MultivariateGaussianMixture: Fits the Gaussian mixture model with the EM algorithm.
fit(int[]) - Static method in class smile.stat.distribution.PoissonDistribution: Estimates the distribution parameters by MLE.
fit(int[]) - Static method in class smile.stat.distribution.ShiftedGeometricDistribution: Estimates the distribution parameters by MLE.
FloatHeapSelect - Class in smile.sort: This class tracks the smallest values seen thus far in a stream of values.
FloatHeapSelect(int) - Constructor for class smile.sort.FloatHeapSelect: Constructor.
FloatHeapSelect(float[]) - Constructor for class smile.sort.FloatHeapSelect: Constructor.
FTest - Class in smile.stat.hypothesis: F test of the hypothesis that two independent samples come from normal distributions with the same variance, against the alternative that they come from normal distributions with different variances.
full - Variable in class smile.math.matrix.SVD: Is this a full decomposition?
Function - Interface in smile.math: An interface representing a univariate real function.

G

g(double[], double[]) - Method in class smile.math.AbstractDifferentiableMultivariateFunction
g(double) - Method in interface smile.math.DifferentiableFunction: Computes the gradient/derivative at x.
g(double[], double[]) - Method in interface smile.math.DifferentiableMultivariateFunction: Computes the value and gradient at x.
g2(double) - Method in interface smile.math.DifferentiableFunction: Compute the second-order derivative at x.
Gamma - Class in smile.math.special: The gamma, digamma, and incomplete gamma functions.
gamma(double) - Static method in class smile.math.special.Gamma: Gamma function.
GammaDistribution - Class in smile.stat.distribution: The Gamma distribution is a continuous probability distributions with a scale parameter θ and a shape parameter k.
GammaDistribution(double, double) - Constructor for class smile.stat.distribution.GammaDistribution: Constructor.
GaussianDistribution - Class in smile.stat.distribution: The normal distribution or Gaussian distribution is a continuous probability distribution that describes data that clusters around a mean.
GaussianDistribution(double, double) - Constructor for class smile.stat.distribution.GaussianDistribution: Constructor
GaussianKernel - Class in smile.math.kernel: The Gaussian Mercer Kernel.
GaussianKernel(double) - Constructor for class smile.math.kernel.GaussianKernel: Constructor.
GaussianMixture - Class in smile.stat.distribution: Finite univariate Gaussian mixture.
GaussianMixture(Mixture.Component...) - Constructor for class smile.stat.distribution.GaussianMixture: Constructor.
GaussianRadialBasis - Class in smile.math.rbf: Gaussian RBF.
GaussianRadialBasis() - Constructor for class smile.math.rbf.GaussianRadialBasis: Constructor.
GaussianRadialBasis(double) - Constructor for class smile.math.rbf.GaussianRadialBasis: Constructor.
GeometricDistribution - Class in smile.stat.distribution: The geometric distribution is a discrete probability distribution of the number X of Bernoulli trials needed to get one success, supported on the set {1, 2, 3, …}.
GeometricDistribution(double) - Constructor for class smile.stat.distribution.GeometricDistribution: Constructor.
get(String) - Method in class smile.hash.PerfectHash: Returns the index of a string.
get(String) - Method in class smile.hash.PerfectMap: Returns the value associated with the key.
get(int) - Method in class smile.math.Complex.Array: Returns the i-th element.
get(int, int) - Method in class smile.math.matrix.BandMatrix
get(int, int) - Method in class smile.math.matrix.JMatrix
get(int, int) - Method in interface smile.math.matrix.Matrix: Returns the entry value at row i and column j.
get(int, int) - Method in class smile.math.matrix.SparseMatrix
get(int) - Method in class smile.sort.DoubleHeapSelect: Returns the i-th smallest value seen so far.
get(int) - Method in class smile.sort.FloatHeapSelect: Returns the i-th smallest value seen so far.
get(int) - Method in class smile.sort.HeapSelect: Returns the i-th smallest value seen so far.
get(int) - Method in class smile.sort.IntHeapSelect: Returns the i-th smallest value seen so far.
get(int, int) - Method in class smile.util.Array2D: Returns A(i, j).
get(int) - Method in class smile.util.DoubleArrayList: Returns the value at the specified position in this list.
get(int, int) - Method in class smile.util.IntArray2D: Returns A(i, j).
get(int) - Method in class smile.util.IntArrayList: Returns the value at the specified position in this list.
get(int) - Method in class smile.util.IntDoubleHashMap: Returns the value to which the specified key is mapped, or Double.NaN if this map contains no mapping for the key.
get(int) - Method in class smile.util.SparseArray: Returns the value of i-th entry.
getAlpha() - Method in class smile.stat.distribution.BetaDistribution: Returns the shape parameter alpha.
getBeta() - Method in class smile.stat.distribution.BetaDistribution: Returns the shape parameter beta.
getD() - Method in class smile.math.matrix.EVD: Returns the block diagonal eigenvalue matrix whose diagonal are the real part of eigenvalues, lower subdiagonal are positive imaginary parts, and upper subdiagonal are negative imaginary parts.
getEigenValues() - Method in class smile.math.matrix.EVD: Returns the eigenvalues, ordered from largest to smallest.
getEigenVectors() - Method in class smile.math.matrix.EVD: Returns the eigenvector matrix, ordered by eigen values from largest to smallest.
getImagEigenValues() - Method in class smile.math.matrix.EVD: Returns the imaginary parts of the eigenvalues, ordered in real part from largest to smallest.
getInstance() - Static method in class smile.math.matrix.BiconjugateGradient: Returns the instance with default settings.
getInstance() - Static method in class smile.stat.distribution.GaussianDistribution
getOmega() - Method in class smile.math.kernel.PearsonKernel: Get the omega parameter.
getQ() - Method in class smile.math.matrix.QR: Returns the orthogonal factor.
getR() - Method in class smile.math.matrix.QR: Returns the upper triangular factor.
getRealEigenValues() - Method in class smile.math.matrix.EVD: Returns the real parts of the eigenvalues, ordered in real part from largest to smallest.
getS() - Method in class smile.math.matrix.SVD: Returns the diagonal matrix of singular values
getSigma() - Method in class smile.math.kernel.PearsonKernel: Get the sigma parameter.
getSingularValues() - Method in class smile.math.matrix.SVD: Returns the one-dimensional array of singular values, ordered by from largest to smallest.
getTestData(String...) - Static method in interface smile.util.Paths: Get the file path of a test sample dataset.
getTestDataLines(String...) - Static method in interface smile.util.Paths: Returns a reader of test data.
getTestDataReader(String...) - Static method in interface smile.util.Paths: Returns a reader of test data.
getU() - Method in class smile.math.matrix.SVD: Returns the left singular vectors
getV() - Method in class smile.math.matrix.SVD: Returns the right singular vectors
GoodTuring(int[], int[], double[]) - Static method in class smile.stat.Stat: Good–Turing frequency estimation.

H

HammingDistance - Class in smile.math.distance: In information theory, the Hamming distance between two strings of equal length is the number of positions for which the corresponding symbols are different.
HammingDistance() - Constructor for class smile.math.distance.HammingDistance: Constructor.
harwell(Path) - Static method in class smile.math.matrix.SparseMatrix: Reads a sparse matrix from a Harwell-Boeing Exchange Format file.
hash128(ByteBuffer, int, int, long, long[]) - Static method in class smile.hash.MurmurHash3: 128-bit MurmurHash3 for x64.
hash32(ByteBuffer, int, int, int) - Static method in class smile.hash.MurmurHash2: 32-bit MurmurHash.
hash32(byte[], int, int, int) - Static method in class smile.hash.MurmurHash3: 32-bit MurmurHash3.
hash64(ByteBuffer, int, int, long) - Static method in class smile.hash.MurmurHash2: 64-bit MurmurHash.
hashCode() - Method in class smile.math.Complex
heapify() - Method in class smile.sort.HeapSelect: In case of avoiding creating new objects frequently, one may check and update the peek object directly and call this method to sort the internal array in heap order.
HeapSelect<T extends java.lang.Comparable<? super T>> - Class in smile.sort: This class tracks the smallest values seen thus far in a stream of values.
HeapSelect(int) - Constructor for class smile.sort.HeapSelect: Constructor.
HeapSelect(T[]) - Constructor for class smile.sort.HeapSelect: Constructor.
HeapSort - Interface in smile.sort: Heapsort is a comparison-based sorting algorithm, and is part of the selection sort family.
HellingerKernel - Class in smile.math.kernel: The Hellinger Mercer Kernel.
HellingerKernel() - Constructor for class smile.math.kernel.HellingerKernel: Constructor.
Histogram - Interface in smile.math: Histogram utilities.
home - Static variable in interface smile.util.Paths: Smile home directory.
HyperbolicTangentKernel - Class in smile.math.kernel: The hyperbolic tangent kernel.
HyperbolicTangentKernel() - Constructor for class smile.math.kernel.HyperbolicTangentKernel: Constructor.
HyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.HyperbolicTangentKernel: Constructor.
HyperGeometricDistribution - Class in smile.stat.distribution: The hypergeometric distribution is a discrete probability distribution that describes the number of successes in a sequence of n draws from a finite population without replacement, just as the binomial distribution describes the number of successes for draws with replacement.
HyperGeometricDistribution(int, int, int) - Constructor for class smile.stat.distribution.HyperGeometricDistribution: Constructor.

I

i - Variable in class smile.math.matrix.SparseMatrix.Entry: The row index.
i - Variable in class smile.util.IntPair
i - Variable in class smile.util.SparseArray.Entry: The index of entry.
im - Variable in class smile.math.Complex: The imaginary part.
improve(double[], double[]) - Method in class smile.math.matrix.BandMatrix: Iteratively improve a solution to linear equations.
increment() - Method in class smile.util.MutableInt: Increment by one.
increment(int) - Method in class smile.util.MutableInt: Increment.
index - Variable in class smile.util.IntSet: Map of values to index.
indexOf(int) - Method in class smile.util.IntSet: Maps the value to index.
insert(int) - Method in class smile.util.PriorityQueue: Insert a new item into queue.
IntArray2D - Class in smile.util: 2-dimensional array of integers.
IntArray2D(int[][]) - Constructor for class smile.util.IntArray2D: Constructor.
IntArray2D(int, int) - Constructor for class smile.util.IntArray2D: Constructor of all-zero matrix.
IntArray2D(int, int, int) - Constructor for class smile.util.IntArray2D: Constructor.
IntArray2D(int, int, int[]) - Constructor for class smile.util.IntArray2D: Constructor.
IntArrayList - Class in smile.util: A resizeable, array-backed list of integer primitives.
IntArrayList() - Constructor for class smile.util.IntArrayList: Constructs an empty list.
IntArrayList(int) - Constructor for class smile.util.IntArrayList: Constructs an empty list with the specified initial capacity.
IntArrayList(int[]) - Constructor for class smile.util.IntArrayList: Constructs a list containing the values of the specified array.
IntDoubleHashMap - Class in smile.util: HashMap for primitive types.
IntDoubleHashMap() - Constructor for class smile.util.IntDoubleHashMap: Constructs an empty HashMap with the default initial capacity (16) and the default load factor (0.75).
IntDoubleHashMap(int, float) - Constructor for class smile.util.IntDoubleHashMap: Constructor.
IntFunction - Interface in smile.math: An interface representing a univariate int function.
IntHashSet - Class in smile.util: HashSet for primitive types.
IntHashSet() - Constructor for class smile.util.IntHashSet: Constructs an empty HashSet with the default initial capacity (16) and the default load factor (0.75).
IntHashSet(int, float) - Constructor for class smile.util.IntHashSet: Constructor.
IntHeapSelect - Class in smile.sort: This class tracks the smallest values seen thus far in a stream of values.
IntHeapSelect(int) - Constructor for class smile.sort.IntHeapSelect: Constructor.
IntHeapSelect(int[]) - Constructor for class smile.sort.IntHeapSelect: Constructor.
IntPair - Class in smile.util: A pair of integer.
IntPair(int, int) - Constructor for class smile.util.IntPair
IntSet - Class in smile.util: A set of integers.
IntSet(int[]) - Constructor for class smile.util.IntSet: Constructor.
inverf(double) - Static method in class smile.math.special.Erf: The inverse error function.
inverfc(double) - Static method in class smile.math.special.Erf: The inverse complementary error function.
inverse() - Method in class smile.math.matrix.Cholesky: Returns the matrix inverse.
inverse() - Method in interface smile.math.matrix.DenseMatrix: Returns the inverse matrix.
inverse(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the inverse matrix.
inverse() - Method in class smile.math.matrix.LU: Returns the matrix inverse.
inverse(double, double) - Static method in interface smile.math.TimeFunction: Returns the inverse learning rate lambda (alpha * C / (C + t)).
InverseMultiquadricRadialBasis - Class in smile.math.rbf: Inverse multiquadric RBF.
InverseMultiquadricRadialBasis() - Constructor for class smile.math.rbf.InverseMultiquadricRadialBasis
InverseMultiquadricRadialBasis(double) - Constructor for class smile.math.rbf.InverseMultiquadricRadialBasis
inverseRegularizedIncompleteBetaFunction(double, double, double) - Static method in class smile.math.special.Beta: Inverse of regularized incomplete beta function.
inverseRegularizedIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma: The inverse of regularized incomplete gamma function.
inverseTransformSampling() - Method in class smile.stat.distribution.AbstractDistribution: Use inverse transform sampling (also known as the inverse probability integral transform or inverse transformation method or Smirnov transform) to draw a sample from the given distribution.
IQAgent - Class in smile.sort: Incremental quantile estimation.
IQAgent() - Constructor for class smile.sort.IQAgent: Constructor.
IQAgent(int) - Constructor for class smile.sort.IQAgent: Constructor.
isEmpty() - Method in class smile.util.DoubleArrayList: Returns true if this list contains no values.
isEmpty() - Method in class smile.util.IntArrayList: Returns true if this list contains no values.
isEmpty() - Method in class smile.util.SparseArray: Returns true if the array is empty.
isInt(double) - Static method in class smile.math.MathEx: Returns true if x is an integer.
isNullOrEmpty(String) - Static method in interface smile.util.Strings: Returns true if the string is null or empty.
isPower2(int) - Static method in class smile.math.MathEx: Returns true if x is a power of 2.
isProbablePrime(long, int) - Static method in class smile.math.MathEx: Returns true if n is probably prime, false if it's definitely composite.
isSingular() - Method in class smile.math.matrix.LU: Returns true if the matrix is singular or false otherwise.
isSingular() - Method in class smile.math.matrix.QR: Returns true if the matrix is singular (not full column rank).
isSymmetric() - Method in class smile.math.matrix.BandMatrix
isSymmetric() - Method in class smile.math.matrix.JMatrix
isSymmetric() - Method in interface smile.math.matrix.Matrix: Returns true if the matrix is symmetric.
isSymmetric() - Method in class smile.math.matrix.SparseMatrix
isZero(float) - Static method in class smile.math.MathEx: Tests if a floating number is zero.
isZero(float, float) - Static method in class smile.math.MathEx: Tests if a floating number is zero with given epsilon.
isZero(double) - Static method in class smile.math.MathEx: Tests if a floating number is zero.
isZero(double, double) - Static method in class smile.math.MathEx: Tests if a floating number is zero with given epsilon.
iterator() - Method in class smile.math.matrix.SparseMatrix: Returns an iterator of nonzero entries.
iterator(int, int) - Method in class smile.math.matrix.SparseMatrix: Returns an iterator of nonzero entries.
iterator() - Method in class smile.util.SparseArray: Returns an iterator of nonzero entries.

J

j - Variable in class smile.math.matrix.SparseMatrix.Entry: The column index.
j - Variable in class smile.util.IntPair
JaccardDistance<T> - Class in smile.math.distance: The Jaccard index, also known as the Jaccard similarity coefficient is a statistic used for comparing the similarity and diversity of sample sets.
JaccardDistance() - Constructor for class smile.math.distance.JaccardDistance: Constructor.
JensenShannonDistance - Class in smile.math.distance: The Jensen-Shannon divergence is a popular method of measuring the similarity between two probability distributions.
JensenShannonDistance() - Constructor for class smile.math.distance.JensenShannonDistance: Constructor.
JensenShannonDivergence(double[], double[]) - Static method in class smile.math.MathEx: Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JensenShannonDivergence(SparseArray, SparseArray) - Static method in class smile.math.MathEx: Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JensenShannonDivergence(double[], SparseArray) - Static method in class smile.math.MathEx: Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JensenShannonDivergence(SparseArray, double[]) - Static method in class smile.math.MathEx: Jensen-Shannon divergence JS(P||Q) = (KL(P||M) + KL(Q||M)) / 2, where M = (P+Q)/2.
JMatrix - Class in smile.math.matrix: A pure Java implementation of DenseMatrix whose data is stored in a single 1D array of doubles in column major order.
JMatrix(double[][]) - Constructor for class smile.math.matrix.JMatrix: Constructor.
JMatrix(double[]) - Constructor for class smile.math.matrix.JMatrix: Constructor of a column vector/matrix with given array as the internal storage.
JMatrix(int, int) - Constructor for class smile.math.matrix.JMatrix: Constructor of all-zero matrix.
JMatrix(int, int, double) - Constructor for class smile.math.matrix.JMatrix: Constructor.
JMatrix(int, int, double[]) - Constructor for class smile.math.matrix.JMatrix: Constructor.

K

k(int[], int[]) - Method in class smile.math.kernel.BinarySparseGaussianKernel
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseLaplacianKernel
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseLinearKernel
k(int[], int[]) - Method in class smile.math.kernel.BinarySparsePolynomialKernel
k(int[], int[]) - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel
k(double[], double[]) - Method in class smile.math.kernel.GaussianKernel
k(double[], double[]) - Method in class smile.math.kernel.HellingerKernel
k(double[], double[]) - Method in class smile.math.kernel.HyperbolicTangentKernel
k(double[], double[]) - Method in class smile.math.kernel.LaplacianKernel
k(double[], double[]) - Method in class smile.math.kernel.LinearKernel
k(T, T) - Method in interface smile.math.kernel.MercerKernel: Kernel function.
k(double[], double[]) - Method in class smile.math.kernel.PearsonKernel
k(double[], double[]) - Method in class smile.math.kernel.PolynomialKernel
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseGaussianKernel
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseHyperbolicTangentKernel
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLaplacianKernel
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseLinearKernel
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparsePolynomialKernel
k(SparseArray, SparseArray) - Method in class smile.math.kernel.SparseThinPlateSplineKernel
k(double[], double[]) - Method in class smile.math.kernel.ThinPlateSplineKernel
k - Variable in class smile.stat.distribution.GammaDistribution: The shape parameter.
k - Variable in class smile.stat.distribution.WeibullDistribution: The shape parameter.
kendall(int[], int[]) - Static method in class smile.math.MathEx: The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.
kendall(float[], float[]) - Static method in class smile.math.MathEx: The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.
kendall(double[], double[]) - Static method in class smile.math.MathEx: The Kendall Tau Rank Correlation Coefficient is used to measure the degree of correspondence between sets of rankings where the measures are not equidistant.
kendall(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest: Kendall rank correlation test.
KernelDensity - Class in smile.stat.distribution: Kernel density estimation is a non-parametric way of estimating the probability density function of a random variable.
KernelDensity(double[]) - Constructor for class smile.stat.distribution.KernelDensity: Constructor.
KernelDensity(double[], double) - Constructor for class smile.stat.distribution.KernelDensity: Constructor.
KSTest - Class in smile.stat.hypothesis: The Kolmogorov-Smirnov test (K-S test) is a form of minimum distance estimation used as a non-parametric test of equality of one-dimensional probability distributions.
KullbackLeiblerDivergence(double[], double[]) - Static method in class smile.math.MathEx: Kullback-Leibler divergence.
KullbackLeiblerDivergence(SparseArray, SparseArray) - Static method in class smile.math.MathEx: Kullback-Leibler divergence.
KullbackLeiblerDivergence(double[], SparseArray) - Static method in class smile.math.MathEx: Kullback-Leibler divergence.
KullbackLeiblerDivergence(SparseArray, double[]) - Static method in class smile.math.MathEx: Kullback-Leibler divergence.

L

L - Variable in class smile.math.matrix.Cholesky: Array for internal storage of decomposition.
L - Variable in class smile.stat.distribution.DiscreteExponentialFamilyMixture: The log-likelihood when the distribution is fit on a sample data.
L - Variable in class smile.stat.distribution.ExponentialFamilyMixture: The log-likelihood when the distribution is fit on a sample data.
L - Variable in class smile.stat.distribution.MultivariateExponentialFamilyMixture: The log-likelihood when the distribution is fit on a sample data.
lambda - Variable in class smile.stat.distribution.ExponentialDistribution: The rate parameter.
lambda - Variable in class smile.stat.distribution.PoissonDistribution: The average number of events per interval.
lambda - Variable in class smile.stat.distribution.WeibullDistribution: The scale parameter.
Lanczos - Class in smile.math.matrix: The Lanczos algorithm is a direct algorithm devised by Cornelius Lanczos that is an adaptation of power methods to find the most useful eigenvalues and eigenvectors of an n^th order linear system with a limited number of operations, m, where m is much smaller than n.
Lanczos() - Constructor for class smile.math.matrix.Lanczos
LaplacianKernel - Class in smile.math.kernel: The Laplacian Kernel.
LaplacianKernel(double) - Constructor for class smile.math.kernel.LaplacianKernel: Constructor.
lchoose(int, int) - Static method in class smile.math.MathEx: The log of n choose k.
ld() - Method in interface smile.math.matrix.DenseMatrix: The LDA (and LDB, LDC, etc.) parameter in BLAS is effectively the stride of the matrix as it is laid out in linear memory.
LeeDistance - Class in smile.math.distance: In coding theory, the Lee distance is a distance between two strings x₁x₂...x_n and y₁y₂...y_n of equal length n over the q-ary alphabet {0,1,...,q-1} of size q ≥ 2, defined as
LeeDistance(int) - Constructor for class smile.math.distance.LeeDistance: Constructor with a given size q of alphabet.
leftPad(String, int, char) - Static method in interface smile.util.Strings: Left pad a String with a specified character.
length - Variable in class smile.math.Complex.Array
length() - Method in class smile.math.matrix.SparseMatrix: Returns the number of nonzero values.
length() - Method in class smile.stat.distribution.BernoulliDistribution
length() - Method in class smile.stat.distribution.BetaDistribution
length() - Method in class smile.stat.distribution.BinomialDistribution
length() - Method in class smile.stat.distribution.ChiSquareDistribution
length() - Method in class smile.stat.distribution.DiscreteMixture
length() - Method in interface smile.stat.distribution.Distribution: The number of parameters of the distribution.
length() - Method in class smile.stat.distribution.EmpiricalDistribution
length() - Method in class smile.stat.distribution.ExponentialDistribution
length() - Method in class smile.stat.distribution.FDistribution
length() - Method in class smile.stat.distribution.GammaDistribution
length() - Method in class smile.stat.distribution.GaussianDistribution
length() - Method in class smile.stat.distribution.GeometricDistribution
length() - Method in class smile.stat.distribution.HyperGeometricDistribution
length() - Method in class smile.stat.distribution.KernelDensity
length() - Method in class smile.stat.distribution.LogisticDistribution
length() - Method in class smile.stat.distribution.LogNormalDistribution
length() - Method in class smile.stat.distribution.Mixture
length() - Method in interface smile.stat.distribution.MultivariateDistribution: The number of parameters of the distribution.
length() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
length() - Method in class smile.stat.distribution.MultivariateMixture
length() - Method in class smile.stat.distribution.NegativeBinomialDistribution
length() - Method in class smile.stat.distribution.PoissonDistribution
length() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
length() - Method in class smile.stat.distribution.TDistribution
length() - Method in class smile.stat.distribution.WeibullDistribution
levenshtein(String, String) - Static method in class smile.math.distance.EditDistance: Levenshtein distance between two strings allows insertion, deletion, or substitution of characters.
levenshtein(char[], char[]) - Static method in class smile.math.distance.EditDistance: Levenshtein distance between two strings allows insertion, deletion, or substitution of characters.
lfactorial(int) - Static method in class smile.math.MathEx: The log of factorial of n.
lgamma(double) - Static method in class smile.math.special.Gamma: The log of the Gamma function.
likelihood(int[]) - Method in class smile.stat.distribution.DiscreteDistribution: The likelihood given a sample set following the distribution.
likelihood(double[]) - Method in interface smile.stat.distribution.Distribution: The likelihood of the sample set following this distribution.
likelihood(double[]) - Method in class smile.stat.distribution.KernelDensity: The likelihood of the samples.
likelihood(double[][]) - Method in interface smile.stat.distribution.MultivariateDistribution: The likelihood of the sample set following this distribution.
linear(double, double) - Static method in interface smile.math.TimeFunction: Returns the linear learning rate lambda (alpha * (1 - t/T)).
LinearKernel - Class in smile.math.kernel: The linear dot product kernel.
LinearKernel() - Constructor for class smile.math.kernel.LinearKernel: Constructor.
LinearSolver - Interface in smile.math.matrix: The interface of the solver of linear system.
log(double) - Static method in class smile.math.MathEx: Returns natural log without underflow.
log1pe(double) - Static method in class smile.math.MathEx: Returns natural log(1+exp(x)) without overflow.
log2(double) - Static method in class smile.math.MathEx: Log of base 2.
logistic(double) - Static method in class smile.math.MathEx: Logistic sigmoid function.
LogisticDistribution - Class in smile.stat.distribution: The logistic distribution is a continuous probability distribution whose cumulative distribution function is the logistic function, which appears in logistic regression and feedforward neural networks.
LogisticDistribution(double, double) - Constructor for class smile.stat.distribution.LogisticDistribution: Constructor.
logLikelihood(int[]) - Method in class smile.stat.distribution.DiscreteDistribution: The likelihood given a sample set following the distribution.
logLikelihood(double[]) - Method in interface smile.stat.distribution.Distribution: The log likelihood of the sample set following this distribution.
logLikelihood(double[]) - Method in class smile.stat.distribution.KernelDensity: The log likelihood of the samples.
logLikelihood(double[][]) - Method in interface smile.stat.distribution.MultivariateDistribution: The log likelihood of the sample set following this distribution.
LogNormalDistribution - Class in smile.stat.distribution: A log-normal distribution is a probability distribution of a random variable whose logarithm is normally distributed.
LogNormalDistribution(double, double) - Constructor for class smile.stat.distribution.LogNormalDistribution: Constructor.
logp(int) - Method in class smile.stat.distribution.BernoulliDistribution
logp(double) - Method in class smile.stat.distribution.BetaDistribution
logp(int) - Method in class smile.stat.distribution.BinomialDistribution
logp(double) - Method in class smile.stat.distribution.ChiSquareDistribution
logp(int) - Method in class smile.stat.distribution.DiscreteDistribution: The probability mass function in log scale.
logp(double) - Method in class smile.stat.distribution.DiscreteDistribution
logp(int) - Method in class smile.stat.distribution.DiscreteMixture
logp(double) - Method in interface smile.stat.distribution.Distribution: The density at x in log scale, which may prevents the underflow problem.
logp(int) - Method in class smile.stat.distribution.EmpiricalDistribution
logp(double) - Method in class smile.stat.distribution.ExponentialDistribution
logp(double) - Method in class smile.stat.distribution.FDistribution
logp(double) - Method in class smile.stat.distribution.GammaDistribution
logp(double) - Method in class smile.stat.distribution.GaussianDistribution
logp(int) - Method in class smile.stat.distribution.GeometricDistribution
logp(int) - Method in class smile.stat.distribution.HyperGeometricDistribution
logp(double) - Method in class smile.stat.distribution.KernelDensity
logp(double) - Method in class smile.stat.distribution.LogisticDistribution
logp(double) - Method in class smile.stat.distribution.LogNormalDistribution
logp(double) - Method in class smile.stat.distribution.Mixture
logp(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution: The density at x in log scale, which may prevents the underflow problem.
logp(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution
logp(double[]) - Method in class smile.stat.distribution.MultivariateMixture
logp(int) - Method in class smile.stat.distribution.NegativeBinomialDistribution
logp(int) - Method in class smile.stat.distribution.PoissonDistribution
logp(int) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
logp(double) - Method in class smile.stat.distribution.TDistribution
logp(double) - Method in class smile.stat.distribution.WeibullDistribution
lower(int) - Method in class smile.util.PriorityQueue: The value of item k is lower (higher priority) now.
lu() - Method in interface smile.math.matrix.DenseMatrix: Returns the LU decomposition.
lu(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the LU decomposition.
lu() - Method in class smile.math.matrix.JMatrix: LU decomposition is computed by a "left-looking", dot-product, Crout/Doolittle algorithm.
LU - Class in smile.math.matrix: For an m-by-n matrix A with m ≥ n, the LU decomposition is an m-by-n unit lower triangular matrix L, an n-by-n upper triangular matrix U, and a permutation vector piv of length m so that A(piv,:) = L*U.
LU(DenseMatrix, int[], int, boolean) - Constructor for class smile.math.matrix.LU: Constructor.
LU(DenseMatrix, int[], boolean) - Constructor for class smile.math.matrix.LU: Constructor.
lu - Variable in class smile.math.matrix.LU: Array for internal storage of decomposition.

M

m - Variable in class smile.math.matrix.SVD: The number of rows.
M(double[], double[]) - Method in class smile.stat.distribution.BetaDistribution
M(double[], double[]) - Method in class smile.stat.distribution.ChiSquareDistribution
M(int[], double[]) - Method in interface smile.stat.distribution.DiscreteExponentialFamily: The M step in the EM algorithm, which depends the specific distribution.
M(double[], double[]) - Method in class smile.stat.distribution.ExponentialDistribution
M(double[], double[]) - Method in interface smile.stat.distribution.ExponentialFamily: The M step in the EM algorithm, which depends the specific distribution.
M(double[], double[]) - Method in class smile.stat.distribution.GammaDistribution
M(double[], double[]) - Method in class smile.stat.distribution.GaussianDistribution
M(int[], double[]) - Method in class smile.stat.distribution.GeometricDistribution
m - Variable in class smile.stat.distribution.HyperGeometricDistribution: The number of defects.
M(double[][], double[]) - Method in interface smile.stat.distribution.MultivariateExponentialFamily: The M step in the EM algorithm, which depends the specific distribution.
M(double[][], double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution
M(int[], double[]) - Method in class smile.stat.distribution.PoissonDistribution
M(int[], double[]) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
MACHEP - Static variable in class smile.math.MathEx: The largest negative integer such that 1.0 + RADIX^MACHEP ≠ 1.0, except that machep is bounded below by -(DIGITS+3)
mad(int[]) - Static method in class smile.math.MathEx: Returns the median absolute deviation (MAD).
mad(float[]) - Static method in class smile.math.MathEx: Returns the median absolute deviation (MAD).
mad(double[]) - Static method in class smile.math.MathEx: Returns the median absolute deviation (MAD).
MahalanobisDistance - Class in smile.math.distance: In statistics, Mahalanobis distance is based on correlations between variables by which different patterns can be identified and analyzed.
MahalanobisDistance(double[][]) - Constructor for class smile.math.distance.MahalanobisDistance: Constructor with given covariance matrix.
ManhattanDistance - Class in smile.math.distance: Manhattan distance, also known as L₁ distance or L₁ norm, is the sum of the (absolute) differences of their coordinates.
ManhattanDistance() - Constructor for class smile.math.distance.ManhattanDistance: Constructor.
ManhattanDistance(double[]) - Constructor for class smile.math.distance.ManhattanDistance: Constructor.
map(int) - Method in class smile.stat.distribution.DiscreteMixture: Returns the index of component with maximum a posteriori probability.
map(double) - Method in class smile.stat.distribution.Mixture: Returns the index of component with maximum a posteriori probability.
map(double[]) - Method in class smile.stat.distribution.MultivariateMixture: Returns the index of component with maximum a posteriori probability.
market(Path) - Static method in interface smile.math.matrix.Matrix: Reads a matrix from a Matrix Market File Format file.
MathEx - Class in smile.math: Extra basic numeric functions.
matrix() - Method in class smile.math.matrix.Cholesky: Returns lower triangular factor.
matrix() - Method in class smile.math.matrix.LU: Returns the LU decomposition matrix.
Matrix - Interface in smile.math.matrix: An abstract interface of matrix.
matrix() - Method in class smile.math.matrix.QR: Returns the QR decomposition matrix.
MatrixElementConsumer - Interface in smile.math.matrix: Functional interface for lambda iteration through a sparse matrix.
MatrixMultiplication<A,B> - Interface in smile.math.matrix: Matrix multiplication interface.
max(int, int, int) - Static method in class smile.math.MathEx: maximum of 3 integers
max(float, float, float) - Static method in class smile.math.MathEx: maximum of 3 floats
max(double, double, double) - Static method in class smile.math.MathEx: maximum of 3 doubles
max(int, int, int, int) - Static method in class smile.math.MathEx: maximum of 4 integers
max(float, float, float, float) - Static method in class smile.math.MathEx: maximum of 4 floats
max(double, double, double, double) - Static method in class smile.math.MathEx: maximum of 4 doubles
max(int[]) - Static method in class smile.math.MathEx: Returns the maximum value of an array.
max(float[]) - Static method in class smile.math.MathEx: Returns the maximum value of an array.
max(double[]) - Static method in class smile.math.MathEx: Returns the maximum value of an array.
max(int[][]) - Static method in class smile.math.MathEx: Returns the maximum of a matrix.
max(double[][]) - Static method in class smile.math.MathEx: Returns the maximum of a matrix.
mean(int[]) - Static method in class smile.math.MathEx: Returns the mean of an array.
mean(float[]) - Static method in class smile.math.MathEx: Returns the mean of an array.
mean(double[]) - Static method in class smile.math.MathEx: Returns the mean of an array.
mean() - Method in class smile.stat.distribution.BernoulliDistribution
mean() - Method in class smile.stat.distribution.BetaDistribution
mean() - Method in class smile.stat.distribution.BinomialDistribution
mean() - Method in class smile.stat.distribution.ChiSquareDistribution
mean() - Method in class smile.stat.distribution.DiscreteMixture
mean() - Method in interface smile.stat.distribution.Distribution: The mean of distribution.
mean() - Method in class smile.stat.distribution.EmpiricalDistribution
mean() - Method in class smile.stat.distribution.ExponentialDistribution
mean() - Method in class smile.stat.distribution.FDistribution
mean() - Method in class smile.stat.distribution.GammaDistribution
mean() - Method in class smile.stat.distribution.GaussianDistribution
mean() - Method in class smile.stat.distribution.GeometricDistribution
mean() - Method in class smile.stat.distribution.HyperGeometricDistribution
mean() - Method in class smile.stat.distribution.KernelDensity
mean() - Method in class smile.stat.distribution.LogisticDistribution
mean() - Method in class smile.stat.distribution.LogNormalDistribution
mean() - Method in class smile.stat.distribution.Mixture
mean() - Method in interface smile.stat.distribution.MultivariateDistribution: The mean vector of distribution.
mean() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
mean() - Method in class smile.stat.distribution.MultivariateMixture
mean() - Method in class smile.stat.distribution.NegativeBinomialDistribution
mean() - Method in class smile.stat.distribution.PoissonDistribution
mean() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
mean() - Method in class smile.stat.distribution.TDistribution
mean() - Method in class smile.stat.distribution.WeibullDistribution
median(int[]) - Static method in class smile.math.MathEx: Find the median of an array of type int.
median(float[]) - Static method in class smile.math.MathEx: Find the median of an array of type float.
median(double[]) - Static method in class smile.math.MathEx: Find the median of an array of type double.
median(T[]) - Static method in class smile.math.MathEx: Find the median of an array of type double.
median(int[]) - Static method in interface smile.sort.QuickSelect: Find the median of an array of type integer.
median(float[]) - Static method in interface smile.sort.QuickSelect: Find the median of an array of type float.
median(double[]) - Static method in interface smile.sort.QuickSelect: Find the median of an array of type double.
median(T[]) - Static method in interface smile.sort.QuickSelect: Find the median of an array of type double.
MercerKernel<T> - Interface in smile.math.kernel: A Mercer Kernel is a kernel that is positive semi-definite.
MersenneTwister - Class in smile.math.random: Mersenne Twister 32-bit.
MersenneTwister() - Constructor for class smile.math.random.MersenneTwister: Constructor.
MersenneTwister(int) - Constructor for class smile.math.random.MersenneTwister: Constructor.
MersenneTwister(long) - Constructor for class smile.math.random.MersenneTwister: Constructor.
MersenneTwister64 - Class in smile.math.random: Mersenne Twister 64-bit.
MersenneTwister64() - Constructor for class smile.math.random.MersenneTwister64: Constructor.
MersenneTwister64(long) - Constructor for class smile.math.random.MersenneTwister64: Constructor.
method - Variable in class smile.stat.hypothesis.ChiSqTest: A character string indicating what type of test was performed.
method - Variable in class smile.stat.hypothesis.CorTest: A character string indicating what type of test was performed.
method - Variable in class smile.stat.hypothesis.KSTest: A character string indicating what type of test was performed.
method - Variable in class smile.stat.hypothesis.TTest: A character string indicating what type of test was performed.
Metric<T> - Interface in smile.math.distance: A metric function defines a distance between elements of a set.
min(int, int, int) - Static method in class smile.math.MathEx: minimum of 3 integers
min(float, float, float) - Static method in class smile.math.MathEx: minimum of 3 floats
min(double, double, double) - Static method in class smile.math.MathEx: minimum of 3 doubles
min(int, int, int, int) - Static method in class smile.math.MathEx: minimum of 4 integers
min(float, float, float, float) - Static method in class smile.math.MathEx: minimum of 4 floats
min(double, double, double, double) - Static method in class smile.math.MathEx: minimum of 4 doubles
min(int[]) - Static method in class smile.math.MathEx: Returns the minimum value of an array.
min(float[]) - Static method in class smile.math.MathEx: Returns the minimum value of an array.
min(double[]) - Static method in class smile.math.MathEx: Returns the minimum value of an array.
min(int[][]) - Static method in class smile.math.MathEx: Returns the minimum of a matrix.
min(double[][]) - Static method in class smile.math.MathEx: Returns the minimum of a matrix.
minimize(DifferentiableMultivariateFunction, int, double[]) - Method in class smile.math.BFGS: This method solves the unconstrained minimization problem
minimize(DifferentiableMultivariateFunction, double[]) - Method in class smile.math.BFGS: This method solves the unconstrained minimization problem
MinkowskiDistance - Class in smile.math.distance: Minkowski distance of order p or L_p-norm, is a generalization of Euclidean distance that is actually L₂-norm.
MinkowskiDistance(int) - Constructor for class smile.math.distance.MinkowskiDistance: Constructor.
MinkowskiDistance(int, double[]) - Constructor for class smile.math.distance.MinkowskiDistance: Constructor.
Mixture - Class in smile.stat.distribution: A finite mixture model is a probabilistic model for density estimation using a mixture distribution.
Mixture(Mixture.Component...) - Constructor for class smile.stat.distribution.Mixture: Constructor.
Mixture.Component - Class in smile.stat.distribution: A component in the mixture distribution is defined by a distribution and its weight in the mixture.
mu - Variable in class smile.stat.distribution.GaussianDistribution: The mean.
mu - Variable in class smile.stat.distribution.LogisticDistribution: The location parameter.
mu - Variable in class smile.stat.distribution.LogNormalDistribution: The mean of normal distribution.
mu - Variable in class smile.stat.distribution.MultivariateGaussianDistribution: The mean vector.
mul(Complex) - Method in class smile.math.Complex: Returns this * b.
mul(int, int, double) - Method in interface smile.math.matrix.DenseMatrix: A[i][j] *= x
mul(DenseMatrix, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: C = A * B
mul(DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: In place element-wise multiplication A = A * B
mul(double, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: Element-wise addition C = A * x
mul(double) - Method in interface smile.math.matrix.DenseMatrix: In place element-wise multiplication A = A * x
mul(int, int, double) - Method in class smile.math.matrix.JMatrix
mul(DenseMatrix) - Method in class smile.math.matrix.JMatrix
mul(JMatrix) - Method in class smile.math.matrix.JMatrix
mul(DenseMatrix, DenseMatrix) - Method in class smile.math.matrix.JMatrix
mul(JMatrix, JMatrix) - Method in class smile.math.matrix.JMatrix
mul(double) - Method in class smile.math.matrix.JMatrix
mul(double, DenseMatrix) - Method in class smile.math.matrix.JMatrix
mul(double, JMatrix) - Method in class smile.math.matrix.JMatrix
mul(int, int, double) - Method in class smile.util.Array2D
mul(Array2D) - Method in class smile.util.Array2D
mul(double) - Method in class smile.util.Array2D
mul(int, int, int) - Method in class smile.util.IntArray2D
mul(IntArray2D) - Method in class smile.util.IntArray2D
mul(int) - Method in class smile.util.IntArray2D
MultiquadricRadialBasis - Class in smile.math.rbf: Multiquadric RBF.
MultiquadricRadialBasis() - Constructor for class smile.math.rbf.MultiquadricRadialBasis: Constructor.
MultiquadricRadialBasis(double) - Constructor for class smile.math.rbf.MultiquadricRadialBasis: Constructor.
MultivariateDistribution - Interface in smile.stat.distribution: Probability distribution of multivariate random variable.
MultivariateExponentialFamily - Interface in smile.stat.distribution: The purpose of this interface is mainly to define the method M that is the Maximization step in the EM algorithm.
MultivariateExponentialFamilyMixture - Class in smile.stat.distribution: The finite mixture of distributions from multivariate exponential family.
MultivariateExponentialFamilyMixture(MultivariateMixture.Component...) - Constructor for class smile.stat.distribution.MultivariateExponentialFamilyMixture: Constructor.
MultivariateFunction - Interface in smile.math: An interface representing a multivariate real function.
MultivariateGaussianDistribution - Class in smile.stat.distribution: Multivariate Gaussian distribution.
MultivariateGaussianDistribution(double[], double) - Constructor for class smile.stat.distribution.MultivariateGaussianDistribution: Constructor.
MultivariateGaussianDistribution(double[], double[]) - Constructor for class smile.stat.distribution.MultivariateGaussianDistribution: Constructor.
MultivariateGaussianDistribution(double[], DenseMatrix) - Constructor for class smile.stat.distribution.MultivariateGaussianDistribution: Constructor.
MultivariateGaussianMixture - Class in smile.stat.distribution: Finite multivariate Gaussian mixture.
MultivariateGaussianMixture(MultivariateMixture.Component...) - Constructor for class smile.stat.distribution.MultivariateGaussianMixture: Constructor.
MultivariateMixture - Class in smile.stat.distribution: The finite mixture of multivariate distributions.
MultivariateMixture(MultivariateMixture.Component...) - Constructor for class smile.stat.distribution.MultivariateMixture: Constructor.
MultivariateMixture.Component - Class in smile.stat.distribution: A component in the mixture distribution is defined by a distribution and its weight in the mixture.
MurmurHash2 - Class in smile.hash: MurmurHash is a very fast, non-cryptographic hash suitable for general hash-based lookup.
MurmurHash2() - Constructor for class smile.hash.MurmurHash2
MurmurHash3 - Class in smile.hash: MurmurHash is a very fast, non-cryptographic hash suitable for general hash-based lookup.
MurmurHash3() - Constructor for class smile.hash.MurmurHash3
MutableInt - Class in smile.util: A mutable int wrapper.
MutableInt() - Constructor for class smile.util.MutableInt: Constructor.
MutableInt(int) - Constructor for class smile.util.MutableInt: Constructor.

N

n - Variable in class smile.math.matrix.SVD: The number of columns.
n - Variable in class smile.stat.distribution.BinomialDistribution: The number of experiments.
N - Variable in class smile.stat.distribution.HyperGeometricDistribution: The number of total samples.
n - Variable in class smile.stat.distribution.HyperGeometricDistribution: The number of draws.
ncols() - Method in class smile.math.matrix.BandMatrix
ncols() - Method in class smile.math.matrix.JMatrix
ncols() - Method in interface smile.math.matrix.Matrix: Returns the number of columns.
ncols() - Method in class smile.math.matrix.SparseMatrix
ncols() - Method in class smile.util.Array2D
ncols() - Method in class smile.util.IntArray2D
NegativeBinomialDistribution - Class in smile.stat.distribution: Negative binomial distribution arises as the probability distribution of the number of successes in a series of independent and identically distributed Bernoulli trials needed to get a specified (non-random) number r of failures.
NegativeBinomialDistribution(double, double) - Constructor for class smile.stat.distribution.NegativeBinomialDistribution: Constructor.
NEGEP - Static variable in class smile.math.MathEx: The largest negative integer such that 1.0 - RADIX^NEGEP ≠ 1.0, except that negeps is bounded below by -(DIGITS+3)
next(int) - Method in class smile.math.random.MersenneTwister
next(int) - Method in class smile.math.random.MersenneTwister64
next(int) - Method in interface smile.math.random.RandomNumberGenerator: Returns up to 32 random bits.
next(int) - Method in class smile.math.random.UniversalGenerator
nextDouble() - Method in class smile.math.random.MersenneTwister
nextDouble() - Method in class smile.math.random.MersenneTwister64
nextDouble() - Method in class smile.math.Random: Generator a random number uniformly distributed in [0, 1).
nextDouble(double, double) - Method in class smile.math.Random: Generate a uniform random number in the range [lo, hi)
nextDouble() - Method in interface smile.math.random.RandomNumberGenerator: Returns the next pseudorandom, uniformly distributed double value between 0.0 and 1.0 from this random number generator's sequence.
nextDouble() - Method in class smile.math.random.UniversalGenerator
nextDoubles(double[]) - Method in class smile.math.random.MersenneTwister
nextDoubles(double[]) - Method in class smile.math.random.MersenneTwister64
nextDoubles(double[]) - Method in class smile.math.Random: Generate n uniform random numbers in the range [0, 1)
nextDoubles(double[], double, double) - Method in class smile.math.Random: Generate n uniform random numbers in the range [lo, hi)
nextDoubles(double[]) - Method in interface smile.math.random.RandomNumberGenerator: Returns a vector of pseudorandom, uniformly distributed double values between 0.0 and 1.0 from this random number generator's sequence.
nextDoubles(double[]) - Method in class smile.math.random.UniversalGenerator
nextInt() - Method in class smile.math.random.MersenneTwister
nextInt(int) - Method in class smile.math.random.MersenneTwister
nextInt() - Method in class smile.math.random.MersenneTwister64
nextInt(int) - Method in class smile.math.random.MersenneTwister64
nextInt() - Method in class smile.math.Random: Returns a random integer.
nextInt(int) - Method in class smile.math.Random: Returns a random integer in [0, n).
nextInt() - Method in interface smile.math.random.RandomNumberGenerator: Returns the next pseudorandom, uniformly distributed int value from this random number generator's sequence.
nextInt(int) - Method in interface smile.math.random.RandomNumberGenerator: Returns a pseudorandom, uniformly distributed int value between 0 (inclusive) and the specified value (exclusive), drawn from this random number generator's sequence.
nextInt() - Method in class smile.math.random.UniversalGenerator
nextInt(int) - Method in class smile.math.random.UniversalGenerator
nextLong() - Method in class smile.math.random.MersenneTwister
nextLong() - Method in class smile.math.random.MersenneTwister64
nextLong() - Method in class smile.math.Random: Returns a random long integer.
nextLong() - Method in interface smile.math.random.RandomNumberGenerator: Returns the next pseudorandom, uniformly distributed long value from this random number generator's sequence.
nextLong() - Method in class smile.math.random.UniversalGenerator
nonzeros() - Method in class smile.math.matrix.SparseMatrix: Provides a stream over all of the non-zero elements of a sparse matrix.
nonzeros(int, int) - Method in class smile.math.matrix.SparseMatrix: Provides a stream over all of the non-zero elements of range of columns of a sparse matrix.
norm(double[]) - Static method in class smile.math.MathEx: L2 vector norm.
norm() - Method in interface smile.math.matrix.DenseMatrix: L2 matrix norm.
norm() - Method in class smile.math.matrix.SVD: Returns the L2 matrix norm.
norm1(double[]) - Static method in class smile.math.MathEx: L1 vector norm.
norm1() - Method in interface smile.math.matrix.DenseMatrix: L1 matrix norm.
norm2(double[]) - Static method in class smile.math.MathEx: L2 vector norm.
norm2() - Method in interface smile.math.matrix.DenseMatrix: L2 matrix norm.
normalize(double[][]) - Static method in class smile.math.MathEx: Unitizes each column of a matrix to unit length (L_2 norm).
normalize(double[][], boolean) - Static method in class smile.math.MathEx: Unitizes each column of a matrix to unit length (L_2 norm).
normFro() - Method in interface smile.math.matrix.DenseMatrix: Frobenius matrix norm.
normInf(double[]) - Static method in class smile.math.MathEx: L-infinity vector norm.
normInf() - Method in interface smile.math.matrix.DenseMatrix: Infinity matrix norm.
nrows() - Method in class smile.math.matrix.BandMatrix
nrows() - Method in class smile.math.matrix.JMatrix
nrows() - Method in interface smile.math.matrix.Matrix: Returns the number of rows.
nrows() - Method in class smile.math.matrix.SparseMatrix
nrows() - Method in class smile.util.Array2D
nrows() - Method in class smile.util.IntArray2D
nu - Variable in class smile.stat.distribution.ChiSquareDistribution: The degrees of freedom.
nu - Variable in class smile.stat.distribution.TDistribution: The degree of freedom.
nu1 - Variable in class smile.stat.distribution.FDistribution: The degrees of freedom of chi-square distribution in numerator.
nu2 - Variable in class smile.stat.distribution.FDistribution: The degrees of freedom chi-square distribution in denominator.
nullity() - Method in class smile.math.matrix.SVD: Returns the dimension of null space.
nullspace() - Method in class smile.math.matrix.SVD: Returns a matrix of which columns give an orthonormal basis for the null space.

O

of(Complex...) - Static method in class smile.math.Complex.Array
of(double) - Static method in class smile.math.Complex: Returns a Complex instance representing the specified value.
of(double, double) - Static method in class smile.math.Complex: Returns a Complex instance representing the specified value.
of(int[]) - Static method in interface smile.math.Histogram: Generate the histogram of given data.
of(float[]) - Static method in interface smile.math.Histogram: Generate the histogram of given data.
of(double[]) - Static method in interface smile.math.Histogram: Generate the histogram of given data.
of(int[], int) - Static method in interface smile.math.Histogram: Generate the histogram of k bins.
of(int[], double[]) - Static method in interface smile.math.Histogram: Generate the histogram of n bins.
of(float[], int) - Static method in interface smile.math.Histogram: Generate the histogram of n bins.
of(float[], float[]) - Static method in interface smile.math.Histogram: Generate the histogram of n bins.
of(double[], int) - Static method in interface smile.math.Histogram: Generate the histogram of n bins.
of(double[], double[]) - Static method in interface smile.math.Histogram: Generate the histogram of n bins.
of(double[][]) - Static method in interface smile.math.matrix.Matrix: Returns an matrix initialized by given two-dimensional array.
of(double[]) - Static method in interface smile.math.matrix.Matrix: Returns a column vector/matrix initialized by given one-dimensional array.
of(int, int, double) - Static method in interface smile.math.matrix.Matrix: Creates a matrix filled with given value.
of(int) - Method in interface smile.math.TimeFunction: Returns the learning rate at a given iteration.
of(int) - Static method in class smile.util.IntSet: Returns an IntSet of [0, k).
of(int[]) - Static method in class smile.util.IntSet: Finds the unique values from samples.
ones(int, int) - Static method in interface smile.math.matrix.Matrix: Return an all-one matrix.
ordinal(int) - Static method in interface smile.util.Strings: Returns the string representation of ordinal number with suffix.

P

p - Variable in class smile.stat.distribution.BernoulliDistribution: Probability of success.
p(int) - Method in class smile.stat.distribution.BernoulliDistribution
p(double) - Method in class smile.stat.distribution.BetaDistribution
p - Variable in class smile.stat.distribution.BinomialDistribution: The probability of success.
p(int) - Method in class smile.stat.distribution.BinomialDistribution
p(double) - Method in class smile.stat.distribution.ChiSquareDistribution
p(int) - Method in class smile.stat.distribution.DiscreteDistribution: The probability mass function.
p(double) - Method in class smile.stat.distribution.DiscreteDistribution
p(int) - Method in class smile.stat.distribution.DiscreteMixture
p(double) - Method in interface smile.stat.distribution.Distribution: The probability density function for continuous distribution or probability mass function for discrete distribution at x.
p - Variable in class smile.stat.distribution.EmpiricalDistribution: The probabilities for each x.
p(int) - Method in class smile.stat.distribution.EmpiricalDistribution
p(double) - Method in class smile.stat.distribution.ExponentialDistribution
p(double) - Method in class smile.stat.distribution.FDistribution
p(double) - Method in class smile.stat.distribution.GammaDistribution
p(double) - Method in class smile.stat.distribution.GaussianDistribution
p - Variable in class smile.stat.distribution.GeometricDistribution: Probability of success on each trial.
p(int) - Method in class smile.stat.distribution.GeometricDistribution
p(int) - Method in class smile.stat.distribution.HyperGeometricDistribution
p(double) - Method in class smile.stat.distribution.KernelDensity
p(double) - Method in class smile.stat.distribution.LogisticDistribution
p(double) - Method in class smile.stat.distribution.LogNormalDistribution
p(double) - Method in class smile.stat.distribution.Mixture
p(double[]) - Method in interface smile.stat.distribution.MultivariateDistribution: The probability density function for continuous distribution or probability mass function for discrete distribution at x.
p(double[]) - Method in class smile.stat.distribution.MultivariateGaussianDistribution
p(double[]) - Method in class smile.stat.distribution.MultivariateMixture
p - Variable in class smile.stat.distribution.NegativeBinomialDistribution: The success probability in each experiment.
p(int) - Method in class smile.stat.distribution.NegativeBinomialDistribution
p(int) - Method in class smile.stat.distribution.PoissonDistribution
p - Variable in class smile.stat.distribution.ShiftedGeometricDistribution: The probability of success.
p(int) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
p(double) - Method in class smile.stat.distribution.TDistribution
p(double) - Method in class smile.stat.distribution.WeibullDistribution
PageRank - Class in smile.math.matrix: PageRank is a link analysis algorithm and it assigns a numerical weighting to each element of a hyperlinked set of documents, such as the World Wide Web, with the purpose of "measuring" its relative importance within the set.
PageRank() - Constructor for class smile.math.matrix.PageRank
pagerank(Matrix) - Static method in class smile.math.matrix.PageRank: Calculate the page rank vector.
pagerank(Matrix, double[]) - Static method in class smile.math.matrix.PageRank: Calculate the page rank vector.
pagerank(Matrix, double[], double, double, int) - Static method in class smile.math.matrix.PageRank: Calculate the page rank vector.
parseDoubleArray(String) - Static method in interface smile.util.Strings: Parses a double array in format '[1.0, 2.0, 3.0]'.
parseIntArray(String) - Static method in interface smile.util.Strings: Parses a double array in format '[1.0, 2.0, 3.0]'.
Paths - Interface in smile.util: Static methods that return a Path by converting a path string or URI.
pdist(double[][]) - Static method in class smile.math.MathEx: Pairwise distance between pairs of objects.
pdist(double[][], double[][], boolean, boolean) - Static method in class smile.math.MathEx: Pairwise distance between pairs of objects.
pearson(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest: Pearson correlation coefficient test.
PearsonKernel - Class in smile.math.kernel: The Pearson Mercer Kernel.
PearsonKernel() - Constructor for class smile.math.kernel.PearsonKernel: Constructor.
PearsonKernel(double, double) - Constructor for class smile.math.kernel.PearsonKernel: Constructor.
peek() - Method in class smile.sort.DoubleHeapSelect: Returns the k-th smallest value seen so far.
peek() - Method in class smile.sort.FloatHeapSelect: Returns the k-th smallest value seen so far.
peek() - Method in class smile.sort.HeapSelect: Returns the k-th smallest value seen so far.
peek() - Method in class smile.sort.IntHeapSelect: Returns the k-th smallest value seen so far.
PerfectHash - Class in smile.hash: A perfect hash of an array of strings to their index in the array.
PerfectHash(String...) - Constructor for class smile.hash.PerfectHash: Constructs the perfect hash of strings.
PerfectHash(int[], String...) - Constructor for class smile.hash.PerfectHash: Constructs the perfect hash of strings.
PerfectMap<T> - Class in smile.hash: Perfect hash based immutable map.
PerfectMap.Builder<T> - Class in smile.hash: Builder of perfect map.
permutate(int) - Static method in class smile.math.MathEx: Generates a permutation of 0, 1, 2, ..., n-1, which is useful for sampling without replacement.
permutate(int[]) - Static method in class smile.math.MathEx: Generates a permutation of given array.
permutate(float[]) - Static method in class smile.math.MathEx: Generates a permutation of given array.
permutate(double[]) - Static method in class smile.math.MathEx: Generates a permutation of given array.
permutate(Object[]) - Static method in class smile.math.MathEx: Generates a permutation of given array.
permutate(int) - Method in class smile.math.Random: Generates a permutation of 0, 1, 2, ..., n-1, which is useful for sampling without replacement.
permutate(int[]) - Method in class smile.math.Random: Generates a permutation of given array.
permutate(float[]) - Method in class smile.math.Random: Generates a permutation of given array.
permutate(double[]) - Method in class smile.math.Random: Generates a permutation of given array.
permutate(Object[]) - Method in class smile.math.Random: Generates a permutation of given array.
phase() - Method in class smile.math.Complex: Returns angle/phase/argument between -pi and pi.
piv - Variable in class smile.math.matrix.LU: Internal storage of pivot vector.
pivsign - Variable in class smile.math.matrix.LU: pivot sign.
PoissonDistribution - Class in smile.stat.distribution: Poisson distribution expresses the probability of a number of events occurring in a fixed period of time if these events occur with a known average rate and independently of the time since the last event.
PoissonDistribution(double) - Constructor for class smile.stat.distribution.PoissonDistribution: Constructor.
poll() - Method in class smile.util.PriorityQueue: Removes and returns the index of item with minimum value (highest priority).
PolynomialKernel - Class in smile.math.kernel: The polynomial kernel.
PolynomialKernel(int) - Constructor for class smile.math.kernel.PolynomialKernel: Constructor with scale 1 and bias 0.
PolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.PolynomialKernel: Constructor.
posteriori(int) - Method in class smile.stat.distribution.DiscreteMixture: Returns the posteriori probabilities.
posteriori(double) - Method in class smile.stat.distribution.Mixture: Returns the posteriori probabilities.
posteriori(double[]) - Method in class smile.stat.distribution.MultivariateMixture: Returns the posteriori probabilities.
pow(double[], double) - Static method in class smile.math.MathEx: Raise each element of an array to a scalar power.
PowerIteration - Class in smile.math.matrix: The power iteration (also known as power method) is an eigenvalue algorithm that will produce the greatest (in absolute value) eigenvalue and a nonzero vector the corresponding eigenvector.
PowerIteration() - Constructor for class smile.math.matrix.PowerIteration
Preconditioner - Interface in smile.math.matrix: The preconditioner matrix in the biconjugate gradient method.
priori - Variable in class smile.stat.distribution.DiscreteMixture.Component: The priori probability of component.
priori - Variable in class smile.stat.distribution.Mixture.Component: The priori probability of component.
priori - Variable in class smile.stat.distribution.MultivariateMixture.Component: The priori probability of component.
PriorityQueue - Class in smile.util: Priority Queue for index items.
PriorityQueue(double[]) - Constructor for class smile.util.PriorityQueue: Constructor.
PriorityQueue(int, double[]) - Constructor for class smile.util.PriorityQueue: Constructor.
probablePrime(long, int) - Static method in class smile.math.MathEx: Returns a probably prime number greater than n.
put(int, double) - Method in class smile.util.IntDoubleHashMap: Associates the specified value with the specified key in this map.
pvalue - Variable in class smile.stat.hypothesis.ChiSqTest: p-value
pvalue - Variable in class smile.stat.hypothesis.CorTest: (two-sided) p-value of test
pvalue - Variable in class smile.stat.hypothesis.FTest: p-value
pvalue - Variable in class smile.stat.hypothesis.KSTest: P-value
pvalue - Variable in class smile.stat.hypothesis.TTest: p-value

Q

q - Variable in class smile.stat.distribution.BernoulliDistribution: Probability of failure.
q1(int[]) - Static method in class smile.math.MathEx: Find the first quantile (p = 1/4) of an array of type int.
q1(float[]) - Static method in class smile.math.MathEx: Find the first quantile (p = 1/4) of an array of type float.
q1(double[]) - Static method in class smile.math.MathEx: Find the first quantile (p = 1/4) of an array of type double.
q1(T[]) - Static method in class smile.math.MathEx: Find the first quantile (p = 1/4) of an array of type double.
q1(int[]) - Static method in interface smile.sort.QuickSelect: Find the first quantile (p = 1/4) of an array of type integer.
q1(float[]) - Static method in interface smile.sort.QuickSelect: Find the first quantile (p = 1/4) of an array of type float.
q1(double[]) - Static method in interface smile.sort.QuickSelect: Find the first quantile (p = 1/4) of an array of type double.
q1(T[]) - Static method in interface smile.sort.QuickSelect: Find the first quantile (p = 1/4) of an array of type double.
q3(int[]) - Static method in class smile.math.MathEx: Find the third quantile (p = 3/4) of an array of type int.
q3(float[]) - Static method in class smile.math.MathEx: Find the third quantile (p = 3/4) of an array of type float.
q3(double[]) - Static method in class smile.math.MathEx: Find the third quantile (p = 3/4) of an array of type double.
q3(T[]) - Static method in class smile.math.MathEx: Find the third quantile (p = 3/4) of an array of type double.
q3(int[]) - Static method in interface smile.sort.QuickSelect: Find the third quantile (p = 3/4) of an array of type integer.
q3(float[]) - Static method in interface smile.sort.QuickSelect: Find the third quantile (p = 3/4) of an array of type float.
q3(double[]) - Static method in interface smile.sort.QuickSelect: Find the third quantile (p = 3/4) of an array of type double.
q3(T[]) - Static method in interface smile.sort.QuickSelect: Find the third quantile (p = 3/4) of an array of type double.
qr() - Method in interface smile.math.matrix.DenseMatrix: Returns the QR decomposition.
qr(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the QR decomposition.
qr() - Method in class smile.math.matrix.JMatrix: QR Decomposition is computed by Householder reflections.
qr(double) - Method in class smile.math.matrix.JMatrix: QR Decomposition is computed by Householder reflections.
QR - Class in smile.math.matrix: For an m-by-n matrix A with m ≥ n, the QR decomposition is an m-by-n orthogonal matrix Q and an n-by-n upper triangular matrix R such that A = Q*R.
QR(DenseMatrix, double[], boolean) - Constructor for class smile.math.matrix.QR: Constructor.
qr - Variable in class smile.math.matrix.QR: Array for internal storage of decomposition.
quantile(double) - Method in class smile.sort.IQAgent: Returns the estimated p-quantile for the data seen so far.
quantile(double, double, double, double) - Method in class smile.stat.distribution.AbstractDistribution: Inversion of CDF by bisection numeric root finding of "cdf(x) = p" for continuous distribution.
quantile(double, double, double) - Method in class smile.stat.distribution.AbstractDistribution: Inversion of CDF by bisection numeric root finding of "cdf(x) = p" for continuous distribution.
quantile(double) - Method in class smile.stat.distribution.BernoulliDistribution
quantile(double) - Method in class smile.stat.distribution.BetaDistribution
quantile(double) - Method in class smile.stat.distribution.BinomialDistribution
quantile(double) - Method in class smile.stat.distribution.ChiSquareDistribution
quantile(double, int, int) - Method in class smile.stat.distribution.DiscreteDistribution: Invertion of cdf by bisection numeric root finding of "cdf(x) = p" for discrete distribution.* Returns integer n such that P(
quantile(double) - Method in class smile.stat.distribution.DiscreteMixture
quantile(double) - Method in interface smile.stat.distribution.Distribution: The quantile, the probability to the left of quantile is p.
quantile(double) - Method in class smile.stat.distribution.EmpiricalDistribution
quantile(double) - Method in class smile.stat.distribution.ExponentialDistribution
quantile(double) - Method in class smile.stat.distribution.FDistribution
quantile(double) - Method in class smile.stat.distribution.GammaDistribution
quantile(double) - Method in class smile.stat.distribution.GaussianDistribution: The quantile, the probability to the left of quantile(p) is p.
quantile(double) - Method in class smile.stat.distribution.GeometricDistribution
quantile(double) - Method in class smile.stat.distribution.HyperGeometricDistribution
quantile(double) - Method in class smile.stat.distribution.KernelDensity: Inverse of CDF.
quantile(double) - Method in class smile.stat.distribution.LogisticDistribution
quantile(double) - Method in class smile.stat.distribution.LogNormalDistribution
quantile(double) - Method in class smile.stat.distribution.Mixture
quantile(double) - Method in class smile.stat.distribution.NegativeBinomialDistribution
quantile(double) - Method in class smile.stat.distribution.PoissonDistribution
quantile(double) - Method in class smile.stat.distribution.ShiftedGeometricDistribution
quantile(double) - Method in class smile.stat.distribution.TDistribution
quantile(double) - Method in class smile.stat.distribution.WeibullDistribution
quantile2tiled(double) - Method in class smile.stat.distribution.TDistribution: Two-tailed quantile.
QuickSelect - Interface in smile.sort: Selection is asking for the k-th smallest element out of n elements.
QuickSort - Class in smile.sort: Quicksort is a well-known sorting algorithm that, on average, makes O(n log n) comparisons to sort n items.

R

r - Variable in class smile.stat.distribution.NegativeBinomialDistribution: The number of failures until the experiment is stopped.
RadialBasisFunction - Interface in smile.math.rbf: A radial basis function (RBF) is a real-valued function whose value depends only on the distance from the origin, so that φ(x)=φ(||x||); or alternatively on the distance from some other point c, called a center, so that φ(x,c)=φ(||x-c||).
RADIX - Static variable in class smile.math.MathEx: The base of the exponent of the double type.
rand() - Method in class smile.stat.distribution.BernoulliDistribution
rand() - Method in class smile.stat.distribution.BetaDistribution
rand() - Method in class smile.stat.distribution.BinomialDistribution: This function generates a random variate with the binomial distribution.
rand() - Method in class smile.stat.distribution.ChiSquareDistribution
rand() - Method in class smile.stat.distribution.DiscreteMixture
rand() - Method in interface smile.stat.distribution.Distribution: Generates a random number following this distribution.
rand(int) - Method in interface smile.stat.distribution.Distribution: Generates a set of random numbers following this distribution.
rand() - Method in class smile.stat.distribution.EmpiricalDistribution
rand() - Method in class smile.stat.distribution.ExponentialDistribution
rand() - Method in class smile.stat.distribution.FDistribution
rand() - Method in class smile.stat.distribution.GammaDistribution: Only support shape parameter k of integer.
rand() - Method in class smile.stat.distribution.GaussianDistribution: Uses the Box-Muller algorithm to transform Random.random()'s into Gaussian deviates.
rand() - Method in class smile.stat.distribution.GeometricDistribution
rand() - Method in class smile.stat.distribution.HyperGeometricDistribution: Uses inversion by chop-down search from the mode when the mean < 20 and the patchwork-rejection method when the mean > 20.
rand() - Method in class smile.stat.distribution.KernelDensity: Random number generator.
rand() - Method in class smile.stat.distribution.LogisticDistribution
rand() - Method in class smile.stat.distribution.LogNormalDistribution
rand() - Method in class smile.stat.distribution.Mixture
rand() - Method in class smile.stat.distribution.MultivariateGaussianDistribution: Generate a random multivariate Gaussian sample.
rand(int) - Method in class smile.stat.distribution.MultivariateGaussianDistribution: Generates a set of random numbers following this distribution.
rand() - Method in class smile.stat.distribution.NegativeBinomialDistribution
rand() - Method in class smile.stat.distribution.PoissonDistribution: This function generates a random variate with the poisson distribution.
rand() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
rand() - Method in class smile.stat.distribution.TDistribution
rand() - Method in class smile.stat.distribution.WeibullDistribution
randi() - Method in class smile.stat.distribution.DiscreteDistribution: Generates an integer random numbers following this discrete distribution.
randi(int) - Method in class smile.stat.distribution.DiscreteDistribution: Generates a set of integer random numbers following this discrete distribution.
randi(int) - Method in class smile.stat.distribution.EmpiricalDistribution
randInverseCDF() - Method in class smile.stat.distribution.GaussianDistribution: Uses Inverse CDF method to generate a Gaussian deviate.
randn(int, int) - Static method in interface smile.math.matrix.Matrix: Returns a random matrix of standard normal distributed values with given mean and standard dev.
randn(int, int, double, double) - Static method in interface smile.math.matrix.Matrix: Returns a random matrix of normal distributed values with given mean and standard dev.
random(double[]) - Static method in class smile.math.MathEx: Given a set of n probabilities, generate a random number in [0, n).
random(double[], int) - Static method in class smile.math.MathEx: Given a set of m probabilities, draw with replacement a set of n random number in [0, m).
random() - Static method in class smile.math.MathEx: Generate a random number in [0, 1).
random(int) - Static method in class smile.math.MathEx: Generate n random numbers in [0, 1).
random(double, double) - Static method in class smile.math.MathEx: Generate a uniform random number in the range [lo, hi).
random(double, double, int) - Static method in class smile.math.MathEx: Generate n uniform random numbers in the range [lo, hi).
Random - Class in smile.math: This is a high quality random number generator as a replacement of the standard Random class of Java system.
Random() - Constructor for class smile.math.Random: Initialize with default random number generator engine.
Random(long) - Constructor for class smile.math.Random: Initialize with given seed for default random number generator engine.
randomInt(int) - Static method in class smile.math.MathEx: Returns a random integer in [0, n).
randomInt(int, int) - Static method in class smile.math.MathEx: Returns a random integer in [lo, hi).
randomLong() - Static method in class smile.math.MathEx: Returns a random long integer.
RandomNumberGenerator - Interface in smile.math.random: Random number generator interface.
range() - Method in class smile.math.matrix.SVD: Returns a matrix of which columns give an orthonormal basis for the range space.
rank() - Method in class smile.math.matrix.SVD: Returns the effective numerical matrix rank.
rbind(int[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by rows.
rbind(float[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by rows.
rbind(double[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by rows.
rbind(String[]...) - Static method in class smile.math.MathEx: Take a sequence of vector arguments and combine by rows.
re - Variable in class smile.math.Complex: The real part.
reciprocal() - Method in class smile.math.Complex: Returns the reciprocal.
regularizedIncompleteBetaFunction(double, double, double) - Static method in class smile.math.special.Beta: Regularized Incomplete Beta function.
regularizedIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma: Regularized Incomplete Gamma Function P(s,x) = ∫₀^x e^-t t^(s-1) dt
regularizedUpperIncompleteGamma(double, double) - Static method in class smile.math.special.Gamma: Regularized Upper/Complementary Incomplete Gamma Function Q(s,x) = 1 - P(s,x) = 1 - ∫₀^x e^-t t^(s-1) dt
rejection(double, double, double) - Method in class smile.stat.distribution.AbstractDistribution: Use the rejection technique to draw a sample from the given distribution.
remove(int) - Method in class smile.util.DoubleArrayList: Removes the value at specified index from the list.
remove(int) - Method in class smile.util.IntArrayList: Removes the value at specified index from the list.
remove(int) - Method in class smile.util.IntDoubleHashMap: Removes the mapping for the specified key from this map if present.
remove(int) - Method in class smile.util.IntHashSet: Removes the specified element from this set if it is present.
remove(int) - Method in class smile.util.SparseArray: Removes an entry.
replaceNaN(double) - Method in interface smile.math.matrix.DenseMatrix: Replaces NaN's with given value.
replaceNaN(double) - Method in class smile.math.matrix.JMatrix
replaceNaN(double) - Method in class smile.util.Array2D
reverse(int[]) - Static method in class smile.math.MathEx: Reverses the order of the elements in the specified array.
reverse(float[]) - Static method in class smile.math.MathEx: Reverses the order of the elements in the specified array.
reverse(double[]) - Static method in class smile.math.MathEx: Reverses the order of the elements in the specified array.
reverse(T[]) - Static method in class smile.math.MathEx: Reverses the order of the elements in the specified array.
rightPad(String, int, char) - Static method in interface smile.util.Strings: Right pad a String with a specified character.
root - Static variable in class smile.math.MathEx: Root finding algorithms.
Root - Class in smile.math: Root finding algorithms.
Root() - Constructor for class smile.math.Root: Constructor with tol = 1E-7 and maxIter = 500.
Root(double, int) - Constructor for class smile.math.Root: Constructor.
round(double, int) - Static method in class smile.math.MathEx: Round a double vale to given digits such as 10^n, where n is a positive or negative integer.
ROUND_STYLE - Static variable in class smile.math.MathEx: Rounding style.
rowMax(int[][]) - Static method in class smile.math.MathEx: Returns the row maximum for a matrix.
rowMax(double[][]) - Static method in class smile.math.MathEx: Returns the row maximum for a matrix.
rowMeans(double[][]) - Static method in class smile.math.MathEx: Returns the row means for a matrix.
rowMeans() - Method in interface smile.math.matrix.DenseMatrix: Returns the mean of each row.
rowMin(int[][]) - Static method in class smile.math.MathEx: Returns the row minimum for a matrix.
rowMin(double[][]) - Static method in class smile.math.MathEx: Returns the row minimum for a matrix.
rowSds(double[][]) - Static method in class smile.math.MathEx: Returns the row standard deviations for a matrix.
rowSds() - Method in interface smile.math.matrix.DenseMatrix: Returns the standard deviations of each row.
rowSums(int[][]) - Static method in class smile.math.MathEx: Returns the row sums for a matrix.
rowSums(double[][]) - Static method in class smile.math.MathEx: Returns the row sums for a matrix.
rowSums() - Method in interface smile.math.matrix.DenseMatrix: Returns the sum of each row.
rutherford(Path) - Static method in class smile.math.matrix.SparseMatrix: Reads a sparse matrix from a Rutherford-Boeing Exchange Format file.

S

s - Variable in class smile.math.matrix.SVD: Array for internal storage of singular values.
scale(double) - Method in class smile.math.Complex: Scalar multiplication.
scale(double[][]) - Static method in class smile.math.MathEx: Scales each column of a matrix to range [0, 1].
scale(double[][], double, double) - Static method in class smile.math.MathEx: Scales each column of a matrix to range [lo, hi].
scale(double, double[]) - Static method in class smile.math.MathEx: Scale each element of an array by a constant x = a * x.
scale(double, double[], double[]) - Static method in class smile.math.MathEx: Scale each element of an array by a constant y = a * x.
scale() - Method in interface smile.math.matrix.DenseMatrix: Centers and scales the columns of matrix.
scale(double[], double[]) - Method in interface smile.math.matrix.DenseMatrix: Centers and scales the columns of matrix.
scale - Variable in class smile.stat.distribution.LogisticDistribution: The scale parameter.
scatter() - Method in class smile.stat.distribution.MultivariateGaussianDistribution: Returns the scatter of distribution, which is defined as |Σ|.
scott(double[]) - Static method in interface smile.math.Histogram: Returns the number of bins by Scott's rule h = 3.5 * σ / (n^1/3).
sd(int[]) - Static method in class smile.math.MathEx: Returns the standard deviation of an array.
sd(float[]) - Static method in class smile.math.MathEx: Returns the standard deviation of an array.
sd(double[]) - Static method in class smile.math.MathEx: Returns the standard deviation of an array.
sd() - Method in class smile.stat.distribution.BinomialDistribution
sd() - Method in class smile.stat.distribution.ChiSquareDistribution
sd() - Method in interface smile.stat.distribution.Distribution: The standard deviation of distribution.
sd() - Method in class smile.stat.distribution.EmpiricalDistribution
sd() - Method in class smile.stat.distribution.ExponentialDistribution
sd() - Method in class smile.stat.distribution.GammaDistribution
sd() - Method in class smile.stat.distribution.GaussianDistribution
sd() - Method in class smile.stat.distribution.GeometricDistribution
sd() - Method in class smile.stat.distribution.KernelDensity
sd() - Method in class smile.stat.distribution.LogisticDistribution
sd() - Method in class smile.stat.distribution.NegativeBinomialDistribution
sd() - Method in class smile.stat.distribution.PoissonDistribution
sd() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
sd() - Method in class smile.stat.distribution.TDistribution
seeds(long, int) - Static method in class smile.math.MathEx: Returns a stream of prime numbers to be used as RNG seeds.
select(int[], int) - Static method in interface smile.sort.QuickSelect: Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.
select(float[], int) - Static method in interface smile.sort.QuickSelect: Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.
select(double[], int) - Static method in interface smile.sort.QuickSelect: Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.
select(T[], int) - Static method in interface smile.sort.QuickSelect: Given k in [0, n-1], returns an array value from arr such that k array values are less than or equal to the one returned.
set(int, Complex) - Method in class smile.math.Complex.Array: Sets the i-th element.
set(int, double) - Method in class smile.math.Complex.Array: Sets the i-th element with a real value.
set(int, int, double) - Method in class smile.math.matrix.BandMatrix
set(int, int, double) - Method in interface smile.math.matrix.DenseMatrix: Set the entry value at row i and column j.
set(int, int, double) - Method in class smile.math.matrix.JMatrix
set(int, int, double) - Method in class smile.util.Array2D: Sets A(i, j).
set(int, double) - Method in class smile.util.DoubleArrayList: Replaces the value at the specified position in this list with the specified value.
set(int, int, int) - Method in class smile.util.IntArray2D: Sets A(i, j).
set(int, int) - Method in class smile.util.IntArrayList: Replaces the value at the specified position in this list with the specified value.
set(int, double) - Method in class smile.util.SparseArray: Sets or add an entry.
setConvergenceTest(int) - Method in class smile.math.matrix.BiconjugateGradient: Sets which convergence test is applied.
setMaxIter(int) - Method in class smile.math.matrix.BiconjugateGradient: Sets the maximum number of allowed iterations.
setOmega(double) - Method in class smile.math.kernel.PearsonKernel: Set the omega parameter.
setPreconditioner(Preconditioner) - Method in class smile.math.matrix.BiconjugateGradient: Sets the preconditioner matrix.
setSeed(long) - Static method in class smile.math.MathEx: Initialize the random generator with a seed.
setSeed() - Static method in class smile.math.MathEx: Initialize the random generator with a random seed from a cryptographically strong random number generator.
setSeed(long) - Method in class smile.math.random.MersenneTwister
setSeed(int) - Method in class smile.math.random.MersenneTwister
setSeed(long) - Method in class smile.math.random.MersenneTwister64
setSeed(long) - Method in interface smile.math.random.RandomNumberGenerator: Initialize the random generator with a seed.
setSeed(long) - Method in class smile.math.Random: Initialize the random generator with a seed.
setSeed(long) - Method in class smile.math.random.UniversalGenerator
setSigma(double) - Method in class smile.math.kernel.PearsonKernel: Set the sigma parameter.
setSymmetric(boolean) - Method in class smile.math.matrix.BandMatrix
setSymmetric(boolean) - Method in class smile.math.matrix.JMatrix
setSymmetric(boolean) - Method in interface smile.math.matrix.Matrix: Sets if the matrix is symmetric.
setSymmetric(boolean) - Method in class smile.math.matrix.SparseMatrix
setTolerance(double) - Method in class smile.math.matrix.BiconjugateGradient: Sets the desired convergence tolerance.
ShellSort - Interface in smile.sort: Shell sort is a generalization of insertion sort.
ShiftedGeometricDistribution - Class in smile.stat.distribution: The "shifted" geometric distribution is a discrete probability distribution of the number of failures before the first success, supported on the set {0, 1, 2, 3, …}.
ShiftedGeometricDistribution(double) - Constructor for class smile.stat.distribution.ShiftedGeometricDistribution: Constructor.
siftDown(int[], int, int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is decreased.
siftDown(float[], int, int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is decreased.
siftDown(double[], int, int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is decreased.
siftDown(T[], int, int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is decreased.
siftUp(int[], int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is increased.
siftUp(float[], int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is increased.
siftUp(double[], int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is increased.
siftUp(T[], int) - Static method in interface smile.sort.Sort: To restore the max-heap condition when a node's priority is increased.
sigma - Variable in class smile.stat.distribution.GaussianDistribution: The standard deviation.
sigma - Variable in class smile.stat.distribution.LogNormalDistribution: The standard deviation of normal distribution.
sigma - Variable in class smile.stat.distribution.MultivariateGaussianDistribution: The covariance matrix.
sin() - Method in class smile.math.Complex: Returns the complex sine.
singular - Variable in class smile.math.matrix.LU: True if the matrix is singular.
singular - Variable in class smile.math.matrix.QR: Indicate if the matrix is singular.
size() - Method in class smile.sort.HeapSelect: Returns the number of objects that have been added into heap.
size() - Method in class smile.stat.distribution.DiscreteMixture: Returns the number of components in the mixture.
size() - Method in class smile.stat.distribution.Mixture: Returns the number of components in the mixture.
size() - Method in class smile.stat.distribution.MultivariateMixture: Returns the number of components in the mixture.
size() - Method in class smile.util.DoubleArrayList: Returns the number of values in the list.
size() - Method in class smile.util.IntArrayList: Returns the number of values in the list.
size() - Method in class smile.util.IntDoubleHashMap: Returns the number of key-value mappings in this map.
size() - Method in class smile.util.IntHashSet: Returns the number of elements in this set.
size() - Method in class smile.util.IntSet: Returns the number of values.
size() - Method in class smile.util.SparseArray: Returns the number of nonzero entries.
slice(E[], int[]) - Static method in class smile.math.MathEx: Returns a slice of data for given indices.
slice(int[], int[]) - Static method in class smile.math.MathEx: Returns a slice of data for given indices.
slice(float[], int[]) - Static method in class smile.math.MathEx: Returns a slice of data for given indices.
slice(double[], int[]) - Static method in class smile.math.MathEx: Returns a slice of data for given indices.
smile.hash - package smile.hash: Hashing functions.
smile.math - package smile.math: Basic mathematical functions, complex, differentiable function interfaces, random number generators, unconstrained optimization, and raw data type (int and double) array lists, etc.
smile.math.distance - package smile.math.distance: Distance and metric measures.
smile.math.kernel - package smile.math.kernel: Mercer kernels.
smile.math.matrix - package smile.math.matrix: Matrix interface, dense and sparse (band or irregular) matrix encapsulation classes, LU, QR, Cholesky, SVD and eigen decompositions, etc.
smile.math.random - package smile.math.random: High quality random number generators as a replacement of the standard Random class of Java system.
smile.math.rbf - package smile.math.rbf: Radial basis functions.
smile.math.special - package smile.math.special: Special mathematical functions including beta, erf, and gamma.
smile.sort - package smile.sort: Sorting algorithms.
smile.stat - package smile.stat
smile.stat.distribution - package smile.stat.distribution: Probability distributions.
smile.stat.hypothesis - package smile.stat.hypothesis: Statistical hypothesis tests.
smile.util - package smile.util: Utility functions.
softmax(double[]) - Static method in class smile.math.MathEx: The softmax function without overflow.
softmax(double[], int) - Static method in class smile.math.MathEx: The softmax function without overflow.
solve(double[], double[], double[], double[]) - Static method in class smile.math.MathEx: Solve the tridiagonal linear set which is of diagonal dominance |b_i| > |a_i| + |c_i|.
solve(double[], double[]) - Method in class smile.math.matrix.BandMatrix: Solve A*x = b.
solve(Matrix, double[], double[]) - Method in class smile.math.matrix.BiconjugateGradient: Solves A * x = b by iterative biconjugate gradient method.
solve(double[]) - Method in class smile.math.matrix.Cholesky: Solve the linear system A * x = b.
solve(DenseMatrix) - Method in class smile.math.matrix.Cholesky: Solve the linear system A * X = B.
solve(double[], double[]) - Method in interface smile.math.matrix.LinearSolver: Solve A*x = b.
solve(double[]) - Method in class smile.math.matrix.LU: Solve A * x = b.
solve(DenseMatrix) - Method in class smile.math.matrix.LU: Solve A * X = B.
solve(double[], double[]) - Method in interface smile.math.matrix.Preconditioner: Solve A_d * x = b for the preconditioner matrix A_d.
solve(double[], double[]) - Method in class smile.math.matrix.QR: Solve the least squares A*x = b.
solve(DenseMatrix) - Method in class smile.math.matrix.QR: Solve the least squares A * X = B.
solve(double[], double[]) - Method in class smile.math.matrix.SVD: Solve the least squares A*x = b.
solve(DenseMatrix) - Method in class smile.math.matrix.SVD: Solve the least squares A * X = B.
sort(double[][]) - Static method in class smile.math.MathEx: Sorts each variable and returns the index of values in ascending order.
sort(double[], double[]) - Static method in class smile.math.matrix.JMatrix: Sort eigenvalues.
sort(double[], double[], DenseMatrix) - Static method in class smile.math.matrix.JMatrix: Sort eigenvalues and eigenvectors.
sort() - Method in class smile.sort.DoubleHeapSelect: Sort the smallest values.
sort() - Method in class smile.sort.FloatHeapSelect: Sort the smallest values.
sort() - Method in class smile.sort.HeapSelect: Sort the smallest values.
sort(int[]) - Static method in interface smile.sort.HeapSort: Sorts the specified array into ascending numerical order.
sort(float[]) - Static method in interface smile.sort.HeapSort: Sorts the specified array into ascending numerical order.
sort(double[]) - Static method in interface smile.sort.HeapSort: Sorts the specified array into ascending numerical order.
sort(T[]) - Static method in interface smile.sort.HeapSort: Sorts the specified array into ascending order.
sort() - Method in class smile.sort.IntHeapSelect: Sort the smallest values.
sort(int[]) - Static method in class smile.sort.QuickSort: Sorts the specified array into ascending numerical order.
sort(int[], int[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(int[], int[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(int[], double[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(int[], double[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(int[], Object[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(int[], Object[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(float[]) - Static method in class smile.sort.QuickSort: Sorts the specified array into ascending numerical order.
sort(float[], int[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(float[], int[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(float[], float[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(float[], float[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(float[], Object[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(float[], Object[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(double[]) - Static method in class smile.sort.QuickSort: Sorts the specified array into ascending numerical order.
sort(double[], int[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(double[], int[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(double[], double[]) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(double[], double[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(double[], Object[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(double[], Object[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(T[]) - Static method in class smile.sort.QuickSort: Sorts the specified array into ascending order.
sort(T[], int[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(T[], int[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(T[], int[], int, Comparator<T>) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(T[], Object[]) - Static method in class smile.sort.QuickSort: Besides sorting the array arr, the array brr will be also rearranged as the same order of arr.
sort(T[], Object[], int) - Static method in class smile.sort.QuickSort: This is an efficient implementation Quick Sort algorithm without recursive.
sort(int[]) - Static method in interface smile.sort.ShellSort: Sorts the specified array into ascending numerical order.
sort(float[]) - Static method in interface smile.sort.ShellSort: Sorts the specified array into ascending numerical order.
sort(double[]) - Static method in interface smile.sort.ShellSort: Sorts the specified array into ascending numerical order.
sort(T[]) - Static method in interface smile.sort.ShellSort: Sorts the specified array into ascending order.
Sort - Interface in smile.sort: Sort algorithm trait that includes useful static functions such as swap and swift up/down used in many sorting algorithms.
sort() - Method in class smile.util.SparseArray: Sorts the array elements such that the indices are in ascending order.
SparseArray - Class in smile.util: Sparse array of double values.
SparseArray() - Constructor for class smile.util.SparseArray: Constructor.
SparseArray(List<SparseArray.Entry>) - Constructor for class smile.util.SparseArray: Constructor.
SparseArray(Stream<SparseArray.Entry>) - Constructor for class smile.util.SparseArray: Constructor.
SparseArray.Entry - Class in smile.util: The entry in a sparse array of double values.
SparseChebyshevDistance - Class in smile.math.distance: Chebyshev distance (or Tchebychev distance), or L_∞ metric is a metric defined on a vector space where the distance between two vectors is the greatest of their differences along any coordinate dimension.
SparseChebyshevDistance() - Constructor for class smile.math.distance.SparseChebyshevDistance: Constructor.
SparseEuclideanDistance - Class in smile.math.distance: Euclidean distance.
SparseEuclideanDistance() - Constructor for class smile.math.distance.SparseEuclideanDistance: Constructor.
SparseEuclideanDistance(double[]) - Constructor for class smile.math.distance.SparseEuclideanDistance: Constructor with a given weight vector.
SparseGaussianKernel - Class in smile.math.kernel: The Gaussian Mercer Kernel.
SparseGaussianKernel(double) - Constructor for class smile.math.kernel.SparseGaussianKernel: Constructor.
SparseHyperbolicTangentKernel - Class in smile.math.kernel: The hyperbolic tangent kernel.
SparseHyperbolicTangentKernel() - Constructor for class smile.math.kernel.SparseHyperbolicTangentKernel: Constructor with scale 1.0 and offset 0.0.
SparseHyperbolicTangentKernel(double, double) - Constructor for class smile.math.kernel.SparseHyperbolicTangentKernel: Constructor.
SparseLaplacianKernel - Class in smile.math.kernel: The Laplacian Kernel.
SparseLaplacianKernel(double) - Constructor for class smile.math.kernel.SparseLaplacianKernel: Constructor.
SparseLinearKernel - Class in smile.math.kernel: The linear dot product kernel on sparse arrays.
SparseLinearKernel() - Constructor for class smile.math.kernel.SparseLinearKernel: Constructor.
SparseManhattanDistance - Class in smile.math.distance: Manhattan distance, also known as L₁ distance or L₁ norm, is the sum of the (absolute) differences of their coordinates.
SparseManhattanDistance() - Constructor for class smile.math.distance.SparseManhattanDistance: Constructor.
SparseManhattanDistance(double[]) - Constructor for class smile.math.distance.SparseManhattanDistance: Constructor.
SparseMatrix - Class in smile.math.matrix: A sparse matrix is a matrix populated primarily with zeros.
SparseMatrix(int, int, double[], int[], int[]) - Constructor for class smile.math.matrix.SparseMatrix: Constructor.
SparseMatrix(double[][]) - Constructor for class smile.math.matrix.SparseMatrix: Constructor.
SparseMatrix(double[][], double) - Constructor for class smile.math.matrix.SparseMatrix: Constructor.
SparseMatrix.Entry - Class in smile.math.matrix: Encapsulates an entry in a matrix for use in streaming.
SparseMinkowskiDistance - Class in smile.math.distance: Minkowski distance of order p or L_p-norm, is a generalization of Euclidean distance that is actually L₂-norm.
SparseMinkowskiDistance(int) - Constructor for class smile.math.distance.SparseMinkowskiDistance: Constructor.
SparseMinkowskiDistance(int, double[]) - Constructor for class smile.math.distance.SparseMinkowskiDistance: Constructor.
SparsePolynomialKernel - Class in smile.math.kernel: The polynomial kernel.
SparsePolynomialKernel(int) - Constructor for class smile.math.kernel.SparsePolynomialKernel: Constructor with scale 1 and bias 0.
SparsePolynomialKernel(int, double, double) - Constructor for class smile.math.kernel.SparsePolynomialKernel: Constructor.
SparseThinPlateSplineKernel - Class in smile.math.kernel: The Thin Plate Spline Kernel.
SparseThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.SparseThinPlateSplineKernel: Constructor.
spearman(int[], int[]) - Static method in class smile.math.MathEx: The Spearman Rank Correlation Coefficient is a form of the Pearson coefficient with the data converted to rankings (ie.
spearman(float[], float[]) - Static method in class smile.math.MathEx: The Spearman Rank Correlation Coefficient is a form of the Pearson coefficient with the data converted to rankings (ie.
spearman(double[], double[]) - Static method in class smile.math.MathEx: The Spearman Rank Correlation Coefficient is a form of the Pearson coefficient with the data converted to rankings (ie.
spearman(double[], double[]) - Static method in class smile.stat.hypothesis.CorTest: Spearman rank correlation coefficient test.
sqr(double) - Static method in class smile.math.MathEx: Returns x * x.
squaredDistance(int[], int[]) - Static method in class smile.math.MathEx: The squared Euclidean distance.
squaredDistance(float[], float[]) - Static method in class smile.math.MathEx: The squared Euclidean distance.
squaredDistance(double[], double[]) - Static method in class smile.math.MathEx: The squared Euclidean distance.
squaredDistance(SparseArray, SparseArray) - Static method in class smile.math.MathEx: The Euclidean distance.
squaredDistanceWithMissingValues(double[], double[]) - Static method in class smile.math.MathEx: The squared Euclidean distance with handling missing values (represented as NaN).
standardize(double[]) - Static method in class smile.math.MathEx: Standardizes an array to mean 0 and variance 1.
standardize(double[][]) - Static method in class smile.math.MathEx: Standardizes each column of a matrix to 0 mean and unit variance.
Stat - Class in smile.stat: Statistical functions or tests.
Stat.chisq - Class in smile.stat: Chi-square test.
Stat.cor - Class in smile.stat: Correlation test.
Stat.F - Class in smile.stat: F-test.
Stat.KS - Class in smile.stat: The Kolmogorov-Smirnov test (K-S test).
Stat.t - Class in smile.stat: t-test.
stream() - Method in class smile.util.DoubleArrayList: Returns the stream of the array list.
stream() - Method in class smile.util.IntArrayList: Returns the stream of the array list.
stream() - Method in class smile.util.SparseArray: Returns the stream of nonzero entries.
Strings - Interface in smile.util: String utility functions.
sturges(int) - Static method in interface smile.math.Histogram: Returns the number of bins by Sturges' rule k = ceil(log2(n) + 1).
sub(Complex) - Method in class smile.math.Complex: Returns this - b.
sub(double[], double[]) - Static method in class smile.math.MathEx: Element-wise subtraction of two arrays y = y - x.
sub(int, int, double) - Method in interface smile.math.matrix.DenseMatrix: A[i][j] -= x
sub(DenseMatrix, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: C = A - B
sub(DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: In place subtraction A = A - B
sub(double, DenseMatrix) - Method in interface smile.math.matrix.DenseMatrix: Element-wise addition C = A - x
sub(double) - Method in interface smile.math.matrix.DenseMatrix: In place element-wise subtraction A = A - x
sub(int, int, double) - Method in class smile.math.matrix.JMatrix
sub(DenseMatrix) - Method in class smile.math.matrix.JMatrix
sub(JMatrix) - Method in class smile.math.matrix.JMatrix
sub(DenseMatrix, DenseMatrix) - Method in class smile.math.matrix.JMatrix
sub(JMatrix, JMatrix) - Method in class smile.math.matrix.JMatrix
sub(double) - Method in class smile.math.matrix.JMatrix
sub(double, DenseMatrix) - Method in class smile.math.matrix.JMatrix
sub(double, JMatrix) - Method in class smile.math.matrix.JMatrix
sub(int, int, double) - Method in class smile.util.Array2D
sub(Array2D) - Method in class smile.util.Array2D
sub(double) - Method in class smile.util.Array2D
sub(int, int, int) - Method in class smile.util.IntArray2D
sub(IntArray2D) - Method in class smile.util.IntArray2D
sub(int) - Method in class smile.util.IntArray2D
submat(int, int, int, int) - Method in interface smile.math.matrix.DenseMatrix: Returns the submatrix which top left at (i, j) and bottom right at (k, l).
sum(byte[]) - Static method in class smile.math.MathEx: Returns the sum of an array.
sum(int[]) - Static method in class smile.math.MathEx: Returns the sum of an array.
sum(float[]) - Static method in class smile.math.MathEx: Returns the sum of an array.
sum(double[]) - Static method in class smile.math.MathEx: Returns the sum of an array.
sum() - Method in interface smile.math.matrix.DenseMatrix: Returns the sum of all elements in the matrix.
sum() - Method in class smile.math.matrix.JMatrix
sum() - Method in class smile.util.Array2D
sum() - Method in class smile.util.IntArray2D
svd() - Method in interface smile.math.matrix.DenseMatrix: Returns the singular value decomposition.
svd(boolean) - Method in interface smile.math.matrix.DenseMatrix: Returns the singular value decomposition.
svd() - Method in class smile.math.matrix.JMatrix
svd(int) - Method in interface smile.math.matrix.Matrix: Find k largest approximate singular triples of a matrix by the Lanczos algorithm.
svd(int, double, int) - Method in interface smile.math.matrix.Matrix: Find k largest approximate singular triples of a matrix by the Lanczos algorithm.
SVD - Class in smile.math.matrix: Singular Value Decomposition.
SVD(DenseMatrix, DenseMatrix, double[]) - Constructor for class smile.math.matrix.SVD: Constructor.
swap(int[], int, int) - Static method in class smile.math.MathEx: Swap two elements of an array.
swap(float[], int, int) - Static method in class smile.math.MathEx: Swap two elements of an array.
swap(double[], int, int) - Static method in class smile.math.MathEx: Swap two elements of an array.
swap(Object[], int, int) - Static method in class smile.math.MathEx: Swap two elements of an array.
swap(int[], int[]) - Static method in class smile.math.MathEx: Swap two arrays.
swap(float[], float[]) - Static method in class smile.math.MathEx: Swap two arrays.
swap(double[], double[]) - Static method in class smile.math.MathEx: Swap two arrays.
swap(E[], E[]) - Static method in class smile.math.MathEx: Swap two arrays.
swap(int[], int, int) - Static method in interface smile.sort.Sort: Swap two positions.
swap(float[], int, int) - Static method in interface smile.sort.Sort: Swap two positions.
swap(double[], int, int) - Static method in interface smile.sort.Sort: Swap two positions.
swap(Object[], int, int) - Static method in interface smile.sort.Sort: Swap two positions.

T

t - Variable in class smile.stat.hypothesis.CorTest: test statistic
t - Variable in class smile.stat.hypothesis.TTest: t-statistic
tan() - Method in class smile.math.Complex: Returns the complex tangent.
tanh(double) - Static method in class smile.math.MathEx: Hyperbolic tangent function.
tau - Variable in class smile.math.matrix.QR: The diagonal of R for this implementation.
TDistribution - Class in smile.stat.distribution: Student's t-distribution (or simply the t-distribution) is a probability distribution that arises in the problem of estimating the mean of a normally distributed population when the sample size is small.
TDistribution(int) - Constructor for class smile.stat.distribution.TDistribution: Constructor.
test(int[], double[]) - Static method in class smile.stat.hypothesis.ChiSqTest: One-sample chisq test.
test(int[], double[], int) - Static method in class smile.stat.hypothesis.ChiSqTest: One-sample chisq test.
test(int[], int[]) - Static method in class smile.stat.hypothesis.ChiSqTest: Two-sample chisq test.
test(int[], int[], int) - Static method in class smile.stat.hypothesis.ChiSqTest: Two-sample chisq test.
test(int[][]) - Static method in class smile.stat.hypothesis.ChiSqTest: Given a two-dimensional contingency table in the form of an array of integers, returns Chi-square test for independence.
test(double[], double[]) - Static method in class smile.stat.hypothesis.FTest: Test if the arrays x and y have significantly different variances.
test(double[], Distribution) - Static method in class smile.stat.hypothesis.KSTest: The one-sample KS test for the null hypothesis that the data set x is drawn from the given distribution.
test(double[], double[]) - Static method in class smile.stat.hypothesis.KSTest: The two-sample KS test for the null hypothesis that the data sets are drawn from the same distribution.
test(double[], double) - Static method in class smile.stat.hypothesis.TTest: Independent one-sample t-test whether the mean of a normally distributed population has a value specified in a null hypothesis.
test(double[], double[]) - Static method in class smile.stat.hypothesis.TTest: Test if the arrays x and y have significantly different means.
test(double[], double[], boolean) - Static method in class smile.stat.hypothesis.TTest: Test if the arrays x and y have significantly different means.
test(double, int) - Static method in class smile.stat.hypothesis.TTest: Test whether the Pearson correlation coefficient, the slope of a regression line, differs significantly from 0.
test(int[], double[]) - Static method in class smile.stat.Stat.chisq: One-sample chisq test.
test(int[], double[], int) - Static method in class smile.stat.Stat.chisq: One-sample chisq test.
test(int[], int[]) - Static method in class smile.stat.Stat.chisq: Two-sample chisq test.
test(int[], int[], int) - Static method in class smile.stat.Stat.chisq: Two-sample chisq test.
test(int[][]) - Static method in class smile.stat.Stat.chisq: Given a two-dimensional contingency table in the form of an array of integers, returns Chi-square test for independence.
test(double[], double[]) - Static method in class smile.stat.Stat.cor: Pearson correlation test.
test(double[], double[], String) - Static method in class smile.stat.Stat.cor: Correlation test.
test(double[], double[]) - Static method in class smile.stat.Stat.F: Test if the arrays x and y have significantly different variances.
test(double[], Distribution) - Static method in class smile.stat.Stat.KS: The one-sample KS test for the null hypothesis that the data set x is drawn from the given distribution.
test(double[], double[]) - Static method in class smile.stat.Stat.KS: The two-sample KS test for the null hypothesis that the data sets are drawn from the same distribution.
test(double[], double) - Static method in class smile.stat.Stat.t: Independent one-sample t-test whether the mean of a normally distributed population has a value specified in a null hypothesis.
test(double[], double[]) - Static method in class smile.stat.Stat.t: Test if the arrays x and y have significantly different means.
test(double[], double[], String) - Static method in class smile.stat.Stat.t: Test if the arrays x and y have significantly different means.
test(double, int) - Static method in class smile.stat.Stat.t: Test whether the Pearson correlation coefficient, the slope of a regression line, differs significantly from 0.
testPaired(double[], double[]) - Static method in class smile.stat.hypothesis.TTest: Given the paired arrays x and y, test if they have significantly different means.
text(Path) - Static method in class smile.math.matrix.SparseMatrix: Reads a sparse matrix from a text file.
theta - Variable in class smile.stat.distribution.GammaDistribution: The scale parameter.
ThinPlateRadialBasis - Class in smile.math.rbf: Thin plate RBF.
ThinPlateRadialBasis() - Constructor for class smile.math.rbf.ThinPlateRadialBasis: Constructor.
ThinPlateRadialBasis(double) - Constructor for class smile.math.rbf.ThinPlateRadialBasis: Constructor.
ThinPlateSplineKernel - Class in smile.math.kernel: The Thin Plate Spline Kernel.
ThinPlateSplineKernel(double) - Constructor for class smile.math.kernel.ThinPlateSplineKernel: Constructor.
TimeFunction - Interface in smile.math: A time-dependent function, e.g.
toArray() - Method in interface smile.math.matrix.DenseMatrix: Return the two-dimensional array of matrix.
toArray() - Method in class smile.sort.HeapSelect: Returns the array back the heap.
toArray(T[]) - Method in class smile.sort.HeapSelect: Returns the array back the heap.
toArray() - Method in class smile.util.DoubleArrayList: Returns an array containing all of the values in this list in proper sequence (from first to last value).
toArray(double[]) - Method in class smile.util.DoubleArrayList: Returns an array containing all of the values in this list in proper sequence (from first to last value).
toArray() - Method in class smile.util.IntArrayList: Returns an array containing all of the values in this list in proper sequence (from first to last value).
toArray(int[]) - Method in class smile.util.IntArrayList: Returns an array containing all of the values in this list in proper sequence (from first to last value).
toArray() - Method in class smile.util.IntHashSet: Returns the elements as an array.
ToFloatFunction<T> - Interface in smile.util
tol - Variable in class smile.math.matrix.SVD: Threshold of estimated roundoff.
toString() - Method in class smile.math.Complex
toString() - Method in class smile.math.distance.ChebyshevDistance
toString() - Method in class smile.math.distance.CorrelationDistance
toString() - Method in class smile.math.distance.DynamicTimeWarping
toString() - Method in class smile.math.distance.EditDistance
toString() - Method in class smile.math.distance.EuclideanDistance
toString() - Method in class smile.math.distance.HammingDistance
toString() - Method in class smile.math.distance.JaccardDistance
toString() - Method in class smile.math.distance.JensenShannonDistance
toString() - Method in class smile.math.distance.LeeDistance
toString() - Method in class smile.math.distance.MahalanobisDistance
toString() - Method in class smile.math.distance.ManhattanDistance
toString() - Method in class smile.math.distance.MinkowskiDistance
toString() - Method in class smile.math.distance.SparseChebyshevDistance
toString() - Method in class smile.math.distance.SparseEuclideanDistance
toString() - Method in class smile.math.distance.SparseManhattanDistance
toString() - Method in class smile.math.distance.SparseMinkowskiDistance
toString() - Method in class smile.math.kernel.BinarySparseGaussianKernel
toString() - Method in class smile.math.kernel.BinarySparseHyperbolicTangentKernel
toString() - Method in class smile.math.kernel.BinarySparseLaplacianKernel
toString() - Method in class smile.math.kernel.BinarySparseLinearKernel
toString() - Method in class smile.math.kernel.BinarySparsePolynomialKernel
toString() - Method in class smile.math.kernel.BinarySparseThinPlateSplineKernel
toString() - Method in class smile.math.kernel.GaussianKernel
toString() - Method in class smile.math.kernel.HellingerKernel
toString() - Method in class smile.math.kernel.HyperbolicTangentKernel
toString() - Method in class smile.math.kernel.LaplacianKernel
toString() - Method in class smile.math.kernel.LinearKernel
toString() - Method in class smile.math.kernel.PearsonKernel
toString() - Method in class smile.math.kernel.PolynomialKernel
toString() - Method in class smile.math.kernel.SparseGaussianKernel
toString() - Method in class smile.math.kernel.SparseHyperbolicTangentKernel
toString() - Method in class smile.math.kernel.SparseLaplacianKernel
toString() - Method in class smile.math.kernel.SparseLinearKernel
toString() - Method in class smile.math.kernel.SparsePolynomialKernel
toString() - Method in class smile.math.kernel.SparseThinPlateSplineKernel
toString() - Method in class smile.math.kernel.ThinPlateSplineKernel
toString() - Method in class smile.math.matrix.JMatrix
toString(boolean) - Method in interface smile.math.matrix.Matrix: Returns the string representation of matrix.
toString(int, int) - Method in interface smile.math.matrix.Matrix: Returns the string representation of matrix.
toString() - Method in class smile.math.matrix.SparseMatrix.Entry
toString() - Method in class smile.math.rbf.GaussianRadialBasis
toString() - Method in class smile.math.rbf.InverseMultiquadricRadialBasis
toString() - Method in class smile.math.rbf.MultiquadricRadialBasis
toString() - Method in class smile.math.rbf.ThinPlateRadialBasis
toString() - Method in class smile.stat.distribution.BernoulliDistribution
toString() - Method in class smile.stat.distribution.BetaDistribution
toString() - Method in class smile.stat.distribution.BinomialDistribution
toString() - Method in class smile.stat.distribution.ChiSquareDistribution
toString() - Method in class smile.stat.distribution.DiscreteMixture
toString() - Method in class smile.stat.distribution.EmpiricalDistribution
toString() - Method in class smile.stat.distribution.ExponentialDistribution
toString() - Method in class smile.stat.distribution.FDistribution
toString() - Method in class smile.stat.distribution.GammaDistribution
toString() - Method in class smile.stat.distribution.GaussianDistribution
toString() - Method in class smile.stat.distribution.GeometricDistribution
toString() - Method in class smile.stat.distribution.HyperGeometricDistribution
toString() - Method in class smile.stat.distribution.LogisticDistribution
toString() - Method in class smile.stat.distribution.LogNormalDistribution
toString() - Method in class smile.stat.distribution.Mixture
toString() - Method in class smile.stat.distribution.MultivariateGaussianDistribution
toString() - Method in class smile.stat.distribution.MultivariateMixture
toString() - Method in class smile.stat.distribution.NegativeBinomialDistribution
toString() - Method in class smile.stat.distribution.PoissonDistribution
toString() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
toString() - Method in class smile.stat.distribution.TDistribution
toString() - Method in class smile.stat.distribution.WeibullDistribution
toString() - Method in class smile.stat.hypothesis.ChiSqTest
toString() - Method in class smile.stat.hypothesis.CorTest
toString() - Method in class smile.stat.hypothesis.FTest
toString() - Method in class smile.stat.hypothesis.KSTest
toString() - Method in class smile.stat.hypothesis.TTest
toString() - Method in class smile.util.Array2D
toString(boolean) - Method in class smile.util.Array2D: Returns the string representation of matrix.
toString(int, int) - Method in class smile.util.Array2D: Returns the string representation of matrix.
toString() - Method in class smile.util.DoubleArrayList
toString() - Method in class smile.util.IntArray2D
toString(boolean) - Method in class smile.util.IntArray2D: Returns the string representation of matrix.
toString(int, int) - Method in class smile.util.IntArray2D: Returns the string representation of matrix.
toString() - Method in class smile.util.IntArrayList
toString() - Method in class smile.util.SparseArray.Entry
toString() - Method in class smile.util.SparseArray
toString(int[]) - Static method in interface smile.util.Strings: Returns the string representation of array in format '[1, 2, 3]'."
toString(double[]) - Static method in interface smile.util.Strings: Returns the string representation of array in format '[1.0, 2.0, 3.0]'."
trace() - Method in interface smile.math.matrix.Matrix: Returns the matrix trace.
transpose(double[][]) - Static method in class smile.math.MathEx: Returns the matrix transpose.
transpose() - Method in class smile.math.matrix.BandMatrix: Returns the matrix transpose.
transpose() - Method in interface smile.math.matrix.DenseMatrix: Returns the matrix transpose.
transpose() - Method in class smile.math.matrix.JMatrix
transpose() - Method in interface smile.math.matrix.Matrix: Returns the matrix transpose.
transpose() - Method in class smile.math.matrix.SparseMatrix
trimToSize() - Method in class smile.util.DoubleArrayList: Trims the capacity to be the list's current size.
trimToSize() - Method in class smile.util.IntArrayList: Trims the capacity to be the list's current size.
TTest - Class in smile.stat.hypothesis: Student's t test.

U

U - Variable in class smile.math.matrix.SVD: Arrays for internal storage of left singular vectors U.
unique(int[]) - Static method in class smile.math.MathEx: Find unique elements of vector.
unique(String[]) - Static method in class smile.math.MathEx: Find unique elements of vector.
unitize(double[]) - Static method in class smile.math.MathEx: Unitize an array so that L2 norm of x = 1.
unitize1(double[]) - Static method in class smile.math.MathEx: Unitize an array so that L1 norm of x is 1.
unitize2(double[]) - Static method in class smile.math.MathEx: Unitize an array so that L2 norm of x = 1.
UniversalGenerator - Class in smile.math.random: The so called "Universal Generator" based on multiplicative congruential method, which originally appeared in "Toward a Universal Random Number Generator" by Marsaglia, Zaman and Tsang.
UniversalGenerator() - Constructor for class smile.math.random.UniversalGenerator: Initialize Random with default seed.
UniversalGenerator(int) - Constructor for class smile.math.random.UniversalGenerator: Initialize Random with a specified integer seed
UniversalGenerator(long) - Constructor for class smile.math.random.UniversalGenerator: Initialize Random with a specified long seed
update(int, Complex) - Method in class smile.math.Complex.Array: Sets the i-th element.
update(int, double) - Method in class smile.math.Complex.Array: Sets the i-th element with a real value.
update(int, int, double) - Method in interface smile.math.matrix.DenseMatrix: Set the entry value at row i and column j.
update(double) - Method in class smile.math.matrix.SparseMatrix.Entry: Update the value of entry in the matrix.
update(double) - Method in class smile.util.SparseArray.Entry: Update the value of entry in the array.

V

V - Variable in class smile.math.matrix.SVD: Arrays for internal storage of right singular vectors V.
value - Variable in class smile.util.MutableInt: The integer value.
valueOf(int) - Method in class smile.util.IntSet: Maps an index to the corresponding value.
values - Variable in class smile.util.IntSet: Map of index to original values.
var(int[]) - Static method in class smile.math.MathEx: Returns the variance of an array.
var(float[]) - Static method in class smile.math.MathEx: Returns the variance of an array.
var(double[]) - Static method in class smile.math.MathEx: Returns the variance of an array.
variance() - Method in class smile.stat.distribution.BernoulliDistribution
variance() - Method in class smile.stat.distribution.BetaDistribution
variance() - Method in class smile.stat.distribution.BinomialDistribution
variance() - Method in class smile.stat.distribution.ChiSquareDistribution
variance() - Method in class smile.stat.distribution.DiscreteMixture
variance() - Method in interface smile.stat.distribution.Distribution: The variance of distribution.
variance() - Method in class smile.stat.distribution.EmpiricalDistribution
variance() - Method in class smile.stat.distribution.ExponentialDistribution
variance() - Method in class smile.stat.distribution.FDistribution
variance() - Method in class smile.stat.distribution.GammaDistribution
variance() - Method in class smile.stat.distribution.GaussianDistribution
variance() - Method in class smile.stat.distribution.GeometricDistribution
variance() - Method in class smile.stat.distribution.HyperGeometricDistribution
variance() - Method in class smile.stat.distribution.KernelDensity
variance() - Method in class smile.stat.distribution.LogisticDistribution
variance() - Method in class smile.stat.distribution.LogNormalDistribution
variance() - Method in class smile.stat.distribution.Mixture
variance() - Method in class smile.stat.distribution.NegativeBinomialDistribution
variance() - Method in class smile.stat.distribution.PoissonDistribution
variance() - Method in class smile.stat.distribution.ShiftedGeometricDistribution
variance() - Method in class smile.stat.distribution.TDistribution
variance() - Method in class smile.stat.distribution.WeibullDistribution

W

WeibullDistribution - Class in smile.stat.distribution: The Weibull distribution is one of the most widely used lifetime distributions in reliability engineering.
WeibullDistribution(double) - Constructor for class smile.stat.distribution.WeibullDistribution: Constructor.
WeibullDistribution(double, double) - Constructor for class smile.stat.distribution.WeibullDistribution: Constructor.
whichMax(int[]) - Static method in class smile.math.MathEx: Returns the index of maximum value of an array.
whichMax(float[]) - Static method in class smile.math.MathEx: Returns the index of maximum value of an array.
whichMax(double[]) - Static method in class smile.math.MathEx: Returns the index of maximum value of an array.
whichMax(double[][]) - Static method in class smile.math.MathEx: Returns the index of maximum value of an array.
whichMin(int[]) - Static method in class smile.math.MathEx: Returns the index of minimum value of an array.
whichMin(float[]) - Static method in class smile.math.MathEx: Returns the index of minimum value of an array.
whichMin(double[]) - Static method in class smile.math.MathEx: Returns the index of minimum value of an array.
whichMin(double[][]) - Static method in class smile.math.MathEx: Returns the index of minimum value of an array.

X

x - Variable in class smile.math.matrix.SparseMatrix.Entry: The value.
x - Variable in class smile.util.SparseArray.Entry: The value of entry.
xax(double[]) - Method in interface smile.math.matrix.DenseMatrix: Returns x' * A * x.

Z

zeros(int, int) - Static method in interface smile.math.matrix.Matrix: Returns all-zero matrix.

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