ProperGeneralizedHyperbolicRNG

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

final
class ProperGeneralizedHyperbolicRNG : NormalVarianceMeanMixtureRNG!T(
T
UniformRNG = Random
) if (
isFloatingPoint!T
) {}

Constructors

this
this(ref UniformRNG rng, T lambda, T eta, T omega, T beta)

Constructor

Examples

import std.algorithm : map;
import std.range;
auto rng = new ProperGeneralizedHyperbolicRNG!double(rndGen, 1.1, 1.1, 1.1, 1.1);
auto sample = rng.map!(x => x + 4).take(9).array;

See Also

Meta