A log normal distribution is distributed such that log X ~ Normal(\mu, \sigma)
- Companion:
- object
Value members
Concrete methods
Computes the cumulative density function of the value x.
Computes the cumulative density function of the value x.
Gets one sample from the distribution. Equivalent to sample()
Gets one sample from the distribution. Equivalent to sample()
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
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
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
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
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