DiracDeltaDistribution

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

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

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

constructor(value: Double)

Properties

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Functions

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open override fun cumulativeProbability(x: Double): Double
open override fun cumulativeProbability(x0: Double, x1: Double): Double
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open override fun density(x: Double): Double
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open override fun getNumericalMean(): Double
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open override fun getNumericalVariance(): Double
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open override fun getSupportLowerBound(): Double
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open override fun getSupportUpperBound(): Double
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open override fun isSupportConnected(): Boolean
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open override fun probability(x: Double): Double
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open override fun reseedRandomGenerator(seed: Long)
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open override fun sample(): Double
open override fun sample(sampleSize: Int): DoubleArray