kmath-stat/space.kscience.kmath.distributions/Distribution1D

Distribution1D

interface Distribution1D<T : Comparable<T>> : Distribution<T> (source)

Inheritors

Functions

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abstract fun cumulative(arg: T): Double

Cumulative distribution for ordered parameter (CDF)

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fun <T : Comparable<T>> Distribution1D<T>.integral(from: T, to: T): Double

Compute probability integral in an interval

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suspend fun <T : Any> Sampler<T>.next(generator: RandomGenerator): T

Samples one value from this Sampler.

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suspend fun Sampler<Double>.nextBuffer(generator: RandomGenerator, size: Int): Buffer<Double>

Samples a Buffer of values from this Sampler.

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abstract fun probability(arg: T): Double

A probability value for given argument arg. For continuous distributions returns PDF

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abstract override fun sample(generator: RandomGenerator): Chain<T>

Generates a chain of samples.

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@JvmName(name = "sampleRealBuffer")
fun Sampler<Double>.sampleBuffer(generator: RandomGenerator, size: Int): Chain<Buffer<Double>>

Generates size real samples and chunks them into some buffers.

@JvmName(name = "sampleIntBuffer")
fun Sampler<Int>.sampleBuffer(generator: RandomGenerator, size: Int): Chain<Buffer<Int>>

Generates size integer samples and chunks them into some buffers.

fun <T : Any> Sampler<T>.sampleBuffer(generator: RandomGenerator, size: Int, bufferFactory: BufferFactory<T> = BufferFactory.boxing()): Chain<Buffer<T>>

Sample a bunch of values