atmosphere.random

Members

Classes

GeneralizedHyperbolicRNG

class GeneralizedHyperbolicRNG(T, UniformRNG = Random)

Class to generate random observations from a generalized hyperbolic distribution using normal variance-mean mixture of generalized inverse Gaussian distribution.

GeneralizedInverseGaussianRNG

class GeneralizedInverseGaussianRNG(T, UniformRNG = Random)

Class to generate random observations from a generalized inverse Gaussian distribution.

GeneralizedVarianceGammaRNG

class GeneralizedVarianceGammaRNG(T, UniformRNG = Random)

Class to generate random observations from a generalized variance-gamma distribution using normal variance-mean mixture of generalized gamma distribution.

HyperbolicAsymmetricTRNG

class HyperbolicAsymmetricTRNG(T, UniformRNG = Random)

Class to generate random observations from a hyperbolic asymmetric t-distribution using normal variance-mean mixture of inverse-gamma distribution.

NormalInverseGaussianRNG

class NormalInverseGaussianRNG(T, UniformRNG = Random)

Class to generate random observations from a normal inverse Gaussian distribution using normal variance-mean mixture of inverse Gaussian distribution.

NormalVarianceMeanMixtureRNG

class NormalVarianceMeanMixtureRNG(T, UniformRNG = Random)

Class to create normal variance-mean mixture random number generators. Assume U has mixing probability density, Y ~ N(0, 1). Class constructs RNG for Z = Y*U^(1/2)+beta*U.

ProperGeneralizedHyperbolicRNG

class ProperGeneralizedHyperbolicRNG(T, UniformRNG = Random)

Class to generate random observations from a proper generalized hyperbolic distribution using normal variance-mean mixture of proper generalized inverse Gaussian distribution.

VarianceGammaRNG

class VarianceGammaRNG(T, UniformRNG = Random)

Class to generate random observations from a variance-gamma distribution using normal variance-mean mixture of gamma distribution.

Functions

rChiSquare

T rChiSquare(T shape)

T rChiSquare(UniformRNG rng, T shape)

Function to generate random observation from a Chi-squared distribution.

rExponential

T rExponential()

T rExponential(UniformRNG rng)

Function to generate random observation from standard exponential distribution.

rGamma

T rGamma(T shape)

T rGamma(UniformRNG rng, T shape)

Function to generate random observation from a gamma distribution.

rGeneralizedGamma

T rGeneralizedGamma(T shape, T power)

T rGeneralizedGamma(UniformRNG rng, T shape, T power)

Function to generate random observation from a generalized gamma distribution.

rInverseGamma

T rInverseGamma(T shape)

T rInverseGamma(UniformRNG rng, T shape)

Function to generate random observation from a inverse-gamma distribution.

rInverseGaussian

T rInverseGaussian(T lambda, T mu)

T rInverseGaussian(UniformRNG rng, T lambda, T mu)

Function to generate random observation from a inverse Gaussian distribution.

rNormal

T rNormal()

T rNormal(UniformRNG rng)

Function to generate random observationb from standard normal distribution.

rStudentT

T rStudentT(T shape)

T rStudentT(UniformRNG rng, T shape)

Function to generate random observation from a Student's t-distribution.

rWeibull

T rWeibull(T shape)

T rWeibull(UniformRNG rng, T power)

Function to generate random observation from a Weibull distribution.

toDistributionRNG

DistributionRNG!F toDistributionRNG(Rng rng)

Interfaces

DistributionRNG

interface DistributionRNG(T)

Interface for infinity input range of random numbers.

Structs

GammaSRNG

struct GammaSRNG(T, UniformRNG = Random)

Class to generate random observations from a gamma distribution.

GeneralizedGammaSRNG

struct GeneralizedGammaSRNG(T, UniformRNG = Random)

Class to generate random observations from a generalized gamma distribution.

InverseGammaSRNG

struct InverseGammaSRNG(T, UniformRNG = Random)

Class to generate random observations from a inverse-gamma distribution.

InverseGaussianSRNG

struct InverseGaussianSRNG(T, UniformRNG = Random)

Class to generate random observations from a inverse Gaussian distribution.

ProperGeneralizedInverseGaussianSRNG

struct ProperGeneralizedInverseGaussianSRNG(T, UniformRNG = Random)

Class to generate random observations from a proper (chi > 0, psi > 0) generalized inverse Gaussian distribution. The algorithm is based on that given by Dagpunar (1989).

• algorithm
• cdf
• derivative
• estimate
• finitemixture
• likelihood
• math
• mixture
• moment
• params
• pdf
• quantile
• random
• statistic
• summation
• utilities