All,
I am using a sum of squared differences in the objective function of an
optimization problem I am doing and I have managed to speed it up using the
outer function versus the nested for loops, but my suspicion is that the
calculation could be done even quicker. Please see the code below for a simple
example. If anyone can point out a faster way I would appreciate it greatly.
Thanks,
Roger
X <- runif(1000)
now <- proc.time()
ans <- 0
for (i in 1:length(X)) {
for (j in 1:length(X)) {
ans <- ans + (X[i]-X[j])*(X[i]-X[j])
}
}
ans
speed <- proc.time() - now; cat(" That took ", round(speed[3],1), " secs.\n",
sep="")
now <- proc.time()
gg <- outer(X, X, FUN="-")
sum(gg*gg)
speed <- proc.time() - now; cat(" That took ", round(speed[3],1), " secs.\n",
sep="")
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