vectorized approach to cumulative sampling

Hi All,

I need to sample a vector ("old"), with replacement, up to the point 
where my vector of samples ("new") sums to a predefined value 
("target"), shortening the last sample if necessary so that the total 
sum ("newsum") of the samples matches the predefined value.

While I can easily do this with a "while" loop (see below for example 
code), because the length of both "old" and "new" may be > 20,000, a 
vectorized approach will save me lots of CPU time.

Any suggestions would be greatly appreciated.

Thanks, Dan

Hi Dan,
You should be able to adapt the following vectorised approach
to your specific needs:

  old<-0.001*(1:1000)
  new<-sample(old,10000,replace=TRUE,prob=p)
  target<-200
  min(which(cumsum(new)>target))

## [1] 385

This took only a fraction of a second on my medium-speed machine.
If you get an "Inf" as result, then 'new' doesn't add up to
'target', so you have to extend it.

Hoping this helps,
Ted.


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Date: 07-Apr-05                                       Time: 22:46:12
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