# Vectorising and loop (was Re: [R] optim "a log-likelihood function")

Zhen Pang nusbj at hotmail.com
Thu Sep 30 04:57:32 CEST 2004

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>From: Sundar Dorai-Raj <sundar.dorai-raj at PDF.COM>
>To: Zhen Pang <nusbj at hotmail.com>
>CC: r-help at stat.math.ethz.ch
>Subject: Vectorising and loop (was Re: [R] optim "a log-likelihood
>function")
>Date: Wed, 29 Sep 2004 18:21:17 -0700
>
>
>
>Zhen Pang wrote:
>
>>
>>I also use optim, however, for my case, can you show some light on
>>avoiding the loop?
>>
>>There are around 200 sets of (i,j,k) where i<=j<=k. 3 situations exist
>>whether "=" hold, I list one for example,
>>
>>                      l<-i:(k-j+i)
>>                      s<-rep(0,k)
>>                      s[l]<-choose(j,i)*choose((k-j),(l-i))/choose(k,l)
>>                      ss<-sum(s*x0)
>>
>>then sum all the log(ss) is my log-liklihood function.
>>
>>One loop from 1 to 200 is inevitable. I have tried to use vector, however,
>>I only can simply to this situation.  Thanks.
>>
>>Regards,
>>
>>Zhen
>>
>
>Zhen,
>   Your question doesn't really have much to do with optim, so I changed
>the subject line.
>
>It's difficult to see what you're trying to accomplish without a complete
>example. Could you post one? Also, for loops are necessarily bad.
>
>One thing to note is that you're better off using lchoose in the above
>code. I.e.
>
>log.s <- lchoose(j, i) + lchoose(k - j, l - i) - lchoose(k, l)
>s[l] <- exp(log.s)
>
>--sundar
>
>
I have a matrix of 200 by 2, namely z, the columns are i and j. K is the
maximum of j.

x0 is a k dimension vector.

ss<-rep(0,200)
for (m in 1:200)
{i<-z[m,1]
j<-z[m,2]
l<-i:(k-j+i)
s<-rep(0,k)
s[l]<-choose(j,i)*choose((k-j),(l-i))/choose(k,l) # we only define some
of s to be non-zero, since dim(l) might be smaller than dim(s)
ss[m]<-sum(s*x0)  # ss[m] is a weighted sum of x0
}
sum(log(ss))

How to avoid the loop of m? I tried to define i<-z[,1] and j<-z[,2], but
failed. Thanks.

Regards,

Zhen

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