urgig | R Documentation |
UNU.RAN random variate generator for the Generalized Inverse Gaussian
Distribution with parameters lambda
and omega
.
It also allows sampling from the truncated distribution.
[Special Generator] – Sampling Function: GIG (generalized inverse Gaussian).
urgig(n, lambda, omega, lb=1.e-12, ub=Inf)
n |
size of required sample. |
lambda |
(strictly positive) shape parameter. |
omega |
(strictly positive) shape parameter. |
lb |
lower bound of (truncated) distribution |
ub |
upper bound of (truncated) distribution |
The Generalized Inverse Gaussian distribution with parameters
lambda
=a and omega
=b
has a density proportional to
f(x) ~ x^(a-1) exp(-(b/2)(x+1/x))
for x ≥ 0, a > 0 and b > 0.
The generation algorithm uses transformed density rejection ‘TDR’. The
parameters lb
and ub
can be used to generate variates from
the distribution truncated to the interval (lb
,ub
).
The generation algorithm works for λ ≥ 1 and ω>0 and for λ>0 and ω ≥ 0.5.
This function is wrapper for the UNU.RAN class in R.
Josef Leydold and Wolfgang H\"ormann unuran@statmath.wu.ac.at.
W. H\"ormann, J. Leydold, and G. Derflinger (2004): Automatic Nonuniform Random Variate Generation. Springer-Verlag, Berlin Heidelberg.
N.L. Johnson, S. Kotz, and N. Balakrishnan (1994): Continuous Univariate Distributions, Volume 1. 2nd edition, John Wiley & Sons, Inc., New York. Chap.15, p.284.
runif
and .Random.seed
about random number
generation and unuran
for the UNU.RAN class.
## Create a sample of size 1000 x <- urgig(n=1000,lambda=2,omega=3)
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