| udgig | R Documentation |
Create UNU.RAN object for a Generalized Inverse Gaussian distribution. Two parametrizations are available.
[Distribution] – Generalized Inverse Gaussian.
udgig(theta, psi, chi, lb=0, ub=Inf)
udgiga(theta, omega, eta=1, lb=0, ub=Inf)
theta |
shape parameter. |
psi, chi |
shape parameters (must be strictly positive). |
omega, eta |
shape parameters (must be strictly positive). |
lb |
lower bound of (truncated) distribution. |
ub |
upper bound of (truncated) distribution. |
The generalized inverse Gaussian distribution with parameters
\theta, \psi, and \chi
has density proportional to
f(x) = x^{\theta-1} \exp\left( -\frac{1}{2} \left(\psi x + \frac{\chi}{x}\right)\right)
where \psi>0 and \chi>0.
An alternative parametrization used parameters
\theta, \omega, and \eta
and has density proportional to
f(x) = x^{\theta-1} \exp\left( -\frac{\omega}{2} \left(\frac{x}{\eta}+\frac{\eta}{x}\right)\right)
The domain of the distribution can be truncated to the
interval (lb,ub).
An object of class "unuran.cont".
These two parametrizations can be converted into each other by means of the following transformations:
\psi = \frac{\omega}{\eta},\;\;\;
\chi = \omega\eta
\omega = \sqrt{\chi\psi},\;\;\;
\eta = \sqrt{\frac{\chi}{\psi}}
Josef Leydold and Wolfgang H\"ormann unuran@statmath.wu.ac.at.
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.
unuran.cont.
## Create distribution object for GIG distribution
distr <- udgig(theta=3, psi=1, chi=1)
## Generate generator object; use method PINV (inversion)
gen <- pinvd.new(distr)
## Draw a sample of size 100
x <- ur(gen,100)
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