I am moving this to r-devel.
The problem and solution below posted on r-help could have been
a bit slicker if %*% worked with multidimensional arrays multiplying
them so that if the first arg is a multidimensional array it is mulitplied
along the last dimension (and first dimension for the second arg).
Then one could have written:
Tbar <- tarray %*% t(wt) / rep(wti, each = 9)
which is a bit nicer than what had to be done, see below, given that %*% only
works with matrices.
I suggest that %*% be so extended to multidimensional arrays. Note
that this is upwardly compatible and all existing cases would continue
to work unchanged.
On 7/16/06, Gabor Grothendieck <[EMAIL PROTECTED]> wrote:
> The double loop is the same as:
>
> Tbar[] <- matrix(tarray, 9) %*% t(wt) / rep(wti, each = 9)
>
>
> On 7/16/06, RAVI VARADHAN <[EMAIL PROTECTED]> wrote:
> > Hi,
> >
> > I have the following piece of code that is part of a larger function. This
> > piece is the most time consuming part of the function, and I would like to
> > make this a bit more efficient. Could anyone suggest a way to do this
> > faster?
> >
> > In particular, I would like to replace the nested "for" loop with a faster
> > construct. I tried things like "kronecker" and "outer" combined with
> > apply, but couldn't get it to work.
> >
> >
> > Here is a sample code:
> >
> > ##########################
> > n <- 120
> > sigerr <- 5
> > covmat <- diag(c(8,6,3.5))
> > mu <- c(105,12,10)
> > mcsamp <- 10000
> >
> > Tbar <- array(0, dim=c(3,3,n))
> >
> > # theta is a mcsamp x 3 matrix
> > theta <- mvrnorm(mcsamp, mu = mu, Sigma = covmat)
> >
> > wt <- matrix(runif(n*mcsamp),n,mcsamp)
> > wti <- apply(wt,1,sum)
> >
> > tarray <- array(apply(theta,1,function(x)outer(x,x)),dim=c(3,3,mcsamp))
> >
> > for (i in 1:n) {
> > for (k in 1:mcsamp) {
> > Tbar[,,i] <- Tbar[,,i] + wt[i,k] * tarray[,,k]
> > }
> > Tbar[,,i] <- Tbar[,,i] / wti[i]
> > }
> >
>
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