Re: [Rd] efficiency of sample() with prob.

From: Prof Brian Ripley <>
Date: Wed 22 Jun 2005 - 20:35:03 GMT

You might recall the message

     R is a collaborative project with many contributors.

We suggest that you take up your own suggestion, research this area and offer the R project the results of your research for consideration as your contribution.

It seems likely that in sample(x, size, replace = TRUE, prob) the optimal method depends on both the size of 'x' and 'size' and perhaps to a lesser extent on 'prob'. (That's what my book on the subject shows.)

On Wed, 22 Jun 2005, Bo Peng wrote:

> On 6/21/05, Vadim Ogranovich <> wrote:
>> In his "Introduction to Probability Models" Sheldon Ross describes (sec
>> 11.4.1, 8th edition) the alias method for such weighted sampling.
>> It is based on some decomposition of the original distribution (the
>> weights) into a mixture of two-point distributions.
> This sounds like Walker's alias method for weighted sampling. I looked
> through Knoth's 'the art of computer programming' and find this
> algorithm. I implemented this one but it is just as efficient as the
> bisection lookup method in my case. The reason is that the setup of
> this algorithm is complicated so it is suited for getting large sample
> from short weighted sequences. Anyway, I do suggest R developers try
> this algorithm for sample with replacement. A sample code can be found
> at
> .
> BTW, does anyone know a quicker algorithm to set up the internal table
> of the alias method?

Quicker than what? See the discussion in my Stochastic Simulation book for `quicker than Walker'.

Brian D. Ripley,        
Professor of Applied Statistics,
University of Oxford,             Tel:  +44 1865 272861 (self)
1 South Parks Road,                     +44 1865 272866 (PA)
Oxford OX1 3TG, UK                Fax:  +44 1865 272595

______________________________________________ mailing list
Received on Thu Jun 23 06:37:17 2005

This archive was generated by hypermail 2.1.8 : Mon 20 Feb 2006 - 03:21:09 GMT