| udig | R Documentation | 
Create UNU.RAN object for a Inverse Gaussian (Wald) distribution
with mean mu and shape parameter lambda.
[Distribution] – Inverse Gaussian (Wald).
udig(mu, lambda, lb=0, ub=Inf)
mu | 
 mean (strictly positive).  | 
lambda | 
 shape parameter (strictly positive).  | 
lb | 
 lower bound of (truncated) distribution.  | 
ub | 
 upper bound of (truncated) distribution.  | 
The inverse Gaussian distribution with mean \mu and shape
parameter \lambda
has density
    f(x) =
    \sqrt{\frac{\lambda}{2 \pi x^3} }
    \exp( -\frac{\lambda (x-\mu)^2}{2\mu^2 x} )
  
where \mu>0 and \lambda>0.
The domain of the distribution can be truncated to the 
interval (lb,ub).
An object of class "unuran.cont".
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. 259.
unuran.cont.
## Create distribution object for inverse Gaussian distribution
distr <- udig(mu=3, lambda=2)
## Generate generator object; use method PINV (inversion)
gen <- pinvd.new(distr)
## Draw a sample of size 100
x <- ur(gen,100)
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.