If you can compute the quantile function of the distribution (i.e., the
inverse of the integral of the pdf), then you can use the probability
integral transform: If U is a U(0,1) random variable and Q is the quantile
function of the distribution F, then Q(U) is a random variable distributed
as F.
This is not necessarily the most efficient way of generating the random
number, but it may be the only way in some cases.
HTH,
Andy
> From: Yan Yu
>
> Hello,
> Is there a function in R to generate random number of any given
> distribution (its pdf is given), besides uniform and gaussian
> distribution?
>
> Thanks,
> yan
------------------------------------------------------------------------------
Notice: This e-mail message, together with any attachments,...{{dropped}}
______________________________________________
[EMAIL PROTECTED] mailing list
https://www.stat.math.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
