KSLCore/ksl.utilities.distributions/CentralMVTDistribution

CentralMVTDistribution

class CentralMVTDistribution(dof: Double, covariances: Array<DoubleArray>, stream: RNStreamIfc = KSLRandom.nextRNStream()) : CentralMVNDistribution

Represents a multi-variate t-distribution with means = 0.0 and the provided covariances. The computed CDF values are to about 2 decimal places using Monte-Carlo integration

Parameters

dof

the degrees of freedom, must be greater than zero

covariances

the variance-covariance matrix, must not be null, must be square and positive definite

stream

the stream for the sampler

Constructors

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constructor(dof: Double, covariances: Array<DoubleArray>, stream: RNStreamIfc = KSLRandom.nextRNStream())

Properties

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val dimension: Int

the dimension of the MV distribution

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val dof: Double
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val mcIntegrationController: MCExperimentSetUpIfc

The user can use this to control the specification of the monte-carlo integration of the CDF.

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Functions

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fun cdf(upperLimit: Double): Double

The probability from -infinity to the upper limit, with the upper limit being the same for all dimensions

fun cdf(integrands: List<Interval>): Double
fun cdf(lowerLimits: DoubleArray, upperLimits: DoubleArray): Double

Evaluation of the integral. Accuracy should be about 7 decimal places

fun cdf(lower: Double, upper: Double): Double

Computes the CDF over the rectangular region

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fun createIntervals(lowerLimit: Double, upperLimit: Double): List<Interval>
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fun createLowerIntervals(lowerLimit: Double): List<Interval>

The upper limit will be Double.POSITIVE_INFINITY

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fun createUpperIntervals(upperLimit: Double): List<Interval>

The lower limit will be Double.NEGATIVE_INFINITY

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open override fun toString(): String