On Sat, 15 Nov 2008, kathie wrote:
Dear R users...
I made the R-code for this triple summation computation
http://www.nabble.com/file/p20517134/a.jpg
-------------------------------------------------
Here is my code..
x=seq(.1,1,.1); l=10
y=seq(1,10); m=10
z=seq(.1,1,.1); n=10
sum(sapply(1:l, function(i) {sum(sapply(1:m, function(j) {sum(sapply(1:n,
function(k){exp(x[i]*y[j]*z[k] )/gamma(y[j]+1)}))^(1.5) }))}))
-------------------------------------------------
In fact, this is a part of optimization and in my real data the number of x
is about 5000. So, I guess if it is vectorized, then the running time could
be shortened.
How could I vectorize this? or any suggestion will be greatly appreciated.
gamma and exp ARE vectorized. Do all the computations in the inner most
loop in a single call, then sum those, then raise to 1.5, then sum the
result
something like
foo <- function(x,y,z) {exp( x * y * z )/gamma( y+1 )}
dat <- expand.grid( x=x, y=y, z=z )
res <- do.call( foo, dat )
sum( rowSums( matrix( res, nc= n) )^1.5 )
[1] 1090.613
HTH,
Chuck
Kathryn Lord
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