public final class ProperGeneralizedHyperbolicRNG(T, UniformRNG = Random) : NormalVarianceMeanMixtureRNG!T
if(isFloatingPoint!T)
Class to generate random observations from a proper generalized hyperbolic distribution using normal variance-mean mixture of proper generalized inverse Gaussian distribution.
See Also:
Example
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;
public this(
ref UniformRNG rng,
T lambda,
T eta,
T omega,
T beta)
Constructor
Parameters
rng | uniform random number generator |
lambda | proper generalized inverse Gaussian parameter lambda |
eta | proper generalized inverse Gaussian scale parameter |
omega | proper generalized inverse Gaussian concetration parameter |
beta | mixture scale parameter: |
Functions
this | Constructor |