MultivariateGaussian

Represents a Gaussian distribution over a single real variable.

trait Product
trait Equals
trait Serializable
class Object
trait Matchable
class Any

Value members

Concrete methods

override def toString(): String
Definition Classes
Any
Definition Classes

Inherited methods

Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here

Overridden by filter/map/flatmap for monadic invocations. Basically, rejeciton samplers will return None here

Inherited from:
Rand
def flatMap[E](f: DenseVector[Double] => Rand[E]): Rand[E]

Converts a random sampler of one type to a random sampler of another type. Examples: randInt(10).flatMap(x => randInt(3 * x.asInstanceOf[Int]) gives a Rand[Int] in the range [0,30] Equivalently, for(x <- randInt(10); y <- randInt(30 *x)) yield y

Converts a random sampler of one type to a random sampler of another type. Examples: randInt(10).flatMap(x => randInt(3 * x.asInstanceOf[Int]) gives a Rand[Int] in the range [0,30] Equivalently, for(x <- randInt(10); y <- randInt(30 *x)) yield y

Value parameters:
f

the transform to apply to the sampled value.

Inherited from:
Rand

Samples one element and qpplies the provided function to it. Despite the name, the function is applied once. Sample usage:

Samples one element and qpplies the provided function to it. Despite the name, the function is applied once. Sample usage:

 for(x <- Rand.uniform) { println(x) } 
Value parameters:
f

the function to be applied

Inherited from:
Rand
Inherited from:
Rand
override def logApply(x: DenseVector[Double]): Double
Definition Classes
Inherited from:
ContinuousDistr
def map[E](f: DenseVector[Double] => E): Rand[E]

Converts a random sampler of one type to a random sampler of another type. Examples: uniform.map(_2) gives a Rand[Double] in the range [0,2] Equivalently, for(x <- uniform) yield 2x

Converts a random sampler of one type to a random sampler of another type. Examples: uniform.map(_2) gives a Rand[Double] in the range [0,2] Equivalently, for(x <- uniform) yield 2x

Value parameters:
f

the transform to apply to the sampled value.

Inherited from:
Rand

Returns the probability density function at that point.

Returns the probability density function at that point.

Inherited from:
ContinuousDistr
Inherited from:
Product

Gets n samples from the distribution.

Gets n samples from the distribution.

Inherited from:
Rand

Gets one sample from the distribution. Equivalent to get()

Gets one sample from the distribution. Equivalent to get()

Inherited from:
Rand

An infinitely long iterator that samples repeatedly from the Rand

An infinitely long iterator that samples repeatedly from the Rand

Returns:

an iterator that repeatedly samples

Inherited from:
Rand
def samplesVector[U >: DenseVector[Double]](size: Int)(implicit m: ClassTag[U]): DenseVector[U]

Return a vector of samples.

Return a vector of samples.

Inherited from:
Rand

Returns the probability density function up to a constant at that point.

Returns the probability density function up to a constant at that point.

Inherited from:
ContinuousDistr

Concrete fields

lazy val entropy: Double
lazy override val logNormalizer: Double

Inherited fields

lazy val normalizer: Double
Inherited from:
ContinuousDistr