Simona -
I don't think preallocating your random variables would make
the code run any faster.
A very simple change that would speed things up a little would
be to replace
simPD.vec[i]=length(R.vec[R.vec<cutoff.])
with
simPD.vec[i] = sum(R.vec < cutoff.)
Since you're using a different set of random numbers for each
element of systemic, I don't see an easy way to vectorize your
code (which doesn't mean that such a way doesn't exist).
- Phil Spector
Statistical Computing Facility
Department of Statistics
UC Berkeley
spec...@stat.berkeley.edu
On Thu, 17 Feb 2011, simona.costa...@ubs.com wrote:
Dear all,
Does anyone have any idea on how to speed up the for() loop below.
Currently it takes approximately 2 minutes and 30 seconds.
Because of the size of Nsim and N, simulating a multivariate normal
(instead of simulating Nsim times a vector of N normal distributions)
would require too much memory space.
Many thanks for your kind help,
Simona
N=3000
PD=runif(N,0,1)
cutoff.=qnorm(PD)
rho.=0.1
Nsim=100000
simPD.vec=0*(1:Nsim)
systemic = rnorm(Nsim,0,1);
for (i in 1:Nsim)
{
R.vec=sqrt(rho.)*systemic[i]+sqrt(1-rho.)*rnorm(N,0,1)
simPD.vec[i]=length(R.vec[R.vec<cutoff.])
}
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