On Fri, 14 Mar 2008, Anup Nandialath wrote:
> Dear friends,
>
> Please find below the code that I have employed for a rejection sampler
> to draw from asymmetric laplace distributions. I was wondering if this
> code can be written more efficiently? Are there more efficient ways of
> drawing random numbers from asymmetric laplace distributions??
>
Usually.
It really helps to "provide commented, minimal, self-contained,
reproducible code" as you are asked, but you have not shown what dal() is.
If dal() is **vectorized**, then a vectorized approach like this will
often work well:
rout <- matrix(0,n)
rejected <- seq(n)
k <- n
while( k > 0 ){
rout[ rejected ] <- rnorm( k )
ratio <- dal(val=rout[ rejected ], p=p)/(s*dnorm(rout[ rejected ]))
alpha <- runif( k , min=0, max=1 )
rejected <- rejected[ alpha >= ratio ]
k <- length( rejected )
}
Obviously, I cannot test this without dal().
HTH,
Chuck
p.s. Putting a limit on iterations is usually a good idea, too.
> Thanks in advance for your help and have a great weekend.
>
> Regards
>
> Anup
>
> ***********************************
> ral <- function(n,p,s=3)
> {
> rout <- matrix(0,n)
> for(i in 1:n)
> {
> repeat
> {
> root <- rnorm(1)
> ratio <- dal(val=root, p=p)/(s*dnorm(root))
> alpha <- runif(1, min=0, max=1)
> if(alpha<ratio)
> {break}
> }
> rout[i,] <- root
> }
> return(rout)}
>
>
>
> ---------------------------------
>
> [[alternative HTML version deleted]]
>
> ______________________________________________
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> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
> and provide commented, minimal, self-contained, reproducible code.
>
Charles C. Berry (858) 534-2098
Dept of Family/Preventive Medicine
E mailto:[EMAIL PROTECTED] UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/ La Jolla, San Diego 92093-0901
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