KSLCore/ksl.utilities.distributions/NegativeBinomial

NegativeBinomial

class NegativeBinomial(theProbSuccess: Double = 0.5, theNumSuccesses: Double = 1.0, name: String? = null) : Distribution, DiscretePMFInRangeDistributionIfc, LossFunctionDistributionIfc, GetRVariableIfc, RVParametersTypeIfc(source)

The number of failures before the rth success in a sequence of independent Bernoulli trials with probability p of success on each trial. The range of this random variable is {0, 1, 2, ....}

Parameters

theProbSuccess

The success probability, must be in range (0,1)

theNumSuccesses

The desired number of successes

name

an optional name/label

Constructors

NegativeBinomial

constructor(parameter: DoubleArray)

Constructs a NegativeBinomial using the supplied parameters

constructor(theProbSuccess: Double = 0.5, theNumSuccesses: Double = 1.0, name: String? = null)

Types

Companion

object Companion

Properties

mode

val mode: Int

the mode of the distribution

numSuccesses

var numSuccesses: Double

the desired number of successes to wait for

probOfFailure

val probOfFailure: Double

the probability of failure, 1-p

probOfSuccess

var probOfSuccess: Double

the probability of success, p

recursiveAlgorithmFlag

var recursiveAlgorithmFlag: 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

cdf

open override fun cdf(x: Double): Double

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

fun cdf(j: Int): Double

Computes the cumulative probability distribution function for given value of failures

firstOrderLossFunction

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)

instance

open override fun instance(): NegativeBinomial

invCDF

open override fun invCDF(p: Double): Double

Provides the inverse cumulative distribution function for the distribution

mean

open override fun mean(): Double

Returns the mean or expected value of a distribution

parameters

open override fun parameters(): DoubleArray

Gets the parameters as an array parameters0 is probability of success parameters1 is number of desired successes

open override fun parameters(params: DoubleArray)

Sets the parameters as an array parameters0 is probability of success parameters1 is number of desired successes

pmf

open override fun pmf(i: Int): Double

Returns the prob of getting x failures before the rth success where r is the desired number of successes parameter

probIn

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.

randomVariable

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

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

secondOrderLossFunction

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)

toString

open override fun toString(): String

variance

open override fun variance(): Double

Returns the variance of the distribution if defined