KSLCore/ksl.utilities.distributions/Binomial

Binomial

class Binomial(pSuccess: Double = 0.5, nTrials: Int = 1, name: String? = null) : Distribution, DiscretePMFInRangeDistributionIfc, LossFunctionDistributionIfc, RVParametersTypeIfc(source)

Constructors

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constructor(pSuccess: Double = 0.5, nTrials: Int = 1, name: String? = null)

Types

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object Companion

Properties

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var numTrials: Int

The number of trials

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var probOfSuccess: Double

The probability of success

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var useRecursiveAlgorithm: Boolean

indicates whether pmf and cdf calculations are done by recursive (iterative) algorithm based on logarithms or via beta incomplete function and binomial coefficients.

Functions

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open override fun cdf(x: Double): Double

Returns the F(x) = Pr{X <= x} where F represents the cumulative distribution function

fun cdf(x: Int): Double
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open override fun firstOrderLossFunction(x: Double): Double

Computes the first order loss function for the function for given value of x, G1(x) = Emax(X-x,0)

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open override fun instance(): Binomial
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open override fun invCDF(p: Double): Double

Provides the inverse cumulative distribution function for the distribution

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open override fun mean(): Double

Returns the mean or expected value of a distribution

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open override fun parameters(): DoubleArray

Gets the parameters

open override fun parameters(params: DoubleArray)

Sets the parameters

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open override fun pmf(i: Int): Double
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open override fun probIn(range: IntRange): Double

Computes the sum of the probabilities over the provided range. If the range is closed a..b then the end point b is included in the sum. If the range is open a..<b then the point b is not included in the sum.

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open override fun randomVariable(streamNumber: Int, streamProvider: RNStreamProviderIfc): BinomialRV

Promises to return a random variable that uses the supplied stream number using the supplied stream provider

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open override fun secondOrderLossFunction(x: Double): Double

Computes the 2nd order loss function for the distribution function for given value of x, G2(x) = (1/2)Emax(X-x,0)*max(X-x-1,0)

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open override fun toString(): String
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open override fun variance(): Double

Returns the variance of the distribution if defined