alchemist/org.apache.commons.math3.distribution/DiracDeltaDistribution

DiracDeltaDistribution

class DiracDeltaDistribution(val value: Double) : RealDistribution, Serializable

Models a Real Distribution backed by a Dirac Delta Function. This is similar to a Logistic probability function with a shape whose value tends to zero.

In practice, samples from this function return the provided value as a constant. The variance is zero, there is no randomness involved, and most of the useful information of a real distribution are actually lost. However, this utility can transform tools meant to work with a probability function in such a way that they work with a constant value (e.g., random walks with a constant step).

Constructors

DiracDeltaDistribution

constructor(randomGenerator: RandomGenerator? = null, value: Double)

This constructor is meant for reflection compatibility only. randomGenerator is unused.

constructor(value: Double)

Properties

val value: Double

Functions

cumulativeProbability

open override fun cumulativeProbability(x: Double): Double

open override fun ~~cumulativeProbability~~(x0: Double, x1: Double): Double

open override fun density(x: Double): Double

getNumericalMean

open override fun getNumericalMean(): Double

getNumericalVariance

open override fun getNumericalVariance(): Double

getSupportLowerBound

open override fun getSupportLowerBound(): Double

getSupportUpperBound

open override fun getSupportUpperBound(): Double

inverseCumulativeProbability

open override fun inverseCumulativeProbability(p: Double): Double

isSupportConnected

open override fun isSupportConnected(): Boolean

isSupportLowerBoundInclusive

open override fun ~~isSupportLowerBoundInclusive~~(): Boolean

isSupportUpperBoundInclusive

open override fun ~~isSupportUpperBoundInclusive~~(): Boolean

open override fun probability(x: Double): Double

reseedRandomGenerator

open override fun reseedRandomGenerator(seed: Long)

open override fun sample(): Double

open override fun sample(sampleSize: Int): DoubleArray