KSLCore/ksl.utilities.distributions/Gamma/Companion

Companion

object Companion

Properties

Link copied to clipboard
const val CHISQ_CDF_SERIES_MAX_ITERATIONS: Int = 500

The maximum number of iterations permitted in the chi-square cdf computation

Link copied to clipboard
const val DEFAULT_MAX_ITERATIONS: Int = 5000
Link copied to clipboard
const val INC_GAMMA_MAX_ITERATIONS: Int = 5000

The maximum number of iterations permitted for the incomplete gamma function evaluation process

Link copied to clipboard
const val X_BIG: Double = 40.0

Functions

Link copied to clipboard
fun digamma(argX: Double): Double

Computes the digamma function Mark Johnson, 2nd September 2007

Link copied to clipboard
fun diGammaFunction(x: Double): Double

Computes the digamma function using AS 103

Link copied to clipboard
fun gammaFunction(x: Double): Double

Computes the gamma function at x

Link copied to clipboard
fun incompleteGammaFunction(x: Double, alpha: Double, maxIterations: Int = INC_GAMMA_MAX_ITERATIONS, eps: Double = KSLMath.defaultNumericalPrecision): Double

Computes the incomplete gamma function at x

Link copied to clipboard
fun invChiSquareDistribution(p: Double, dof: Double, maxSeriesIterations: Int = CHISQ_CDF_SERIES_MAX_ITERATIONS, maxIncGammaIterations: Int = INC_GAMMA_MAX_ITERATIONS, EPS: Double = KSLMath.defaultNumericalPrecision): Double

Algorithm AS 91 Appl. Statist. (1975) Vol.24, P.35

Link copied to clipboard
fun logGammaFunction(x: Double): Double

Computes the natural logarithm of the gamma function at x. Useful when x gets large.

Link copied to clipboard
fun parametersFromMeanAndVariance(mean: Double, variance: Double): DoubleArray

Computes the parameters (shape and scale) by matching to mean and variance element0 = shape element1 = scale

Link copied to clipboard
fun parametersFromMoments(vararg moments: Double): DoubleArray

Computes the parameters (shape and scale) by matching to mean and variance element0 = shape element1 = scale