[R] Rejection sampling to draw from distributions

[Charles C. Berry]

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)}
>
>
>
> ---------------------------------
>
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>
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> and provide commented, minimal, self-contained, reproducible code.
>

Charles C. Berry                            (858) 534-2098
                                             Dept of Family/Preventive Medicine
E mailto:cberry at tajo.ucsd.edu	            UC San Diego
http://famprevmed.ucsd.edu/faculty/cberry/  La Jolla, San Diego 92093-0901