Tsjerk,
It seems to me that memory and not time is your big efficiency problem, and I've showed you how to avoid storing your entire input.
If you want to avoid doing each multiplication twice, you can replace the "outer" with a function that computes each product only once and accumulate sums of those products.
Iii = matrix(c(rep(1:200,200),rep(1:200,each=200)), ncol=2)
Iii = iii[ iii[,1]<=iii[,2]]

and at each step

V2 = v2+X[iii[,1]] * X[iii[,2]]

instead of M.

I would imagine that the internal cov does this anyway, as you are not the first person to notice this symmetry, so I'm not sure of the point of this exercise.

PS: I actually know how to spell and pronounce Tsjerk, but Tsj is not a very familiar pattern for my fingers.

From: Tsjerk Wassenaar [mailto:tsjerkw@gmail.com]
Sent: Monday, March 14, 2011 1:41 PM
To: Dwyer Rex USRE
Subject: Re: RE: [R] *Building* a covariance matrix efficiently


Hi Rex,

Thanks for the reply. But it doesn't solve the issues of redundant calculations due to symmetry, both in the outer product and in the summation.

Cheers,

Tsjerk (correct spelling, really)
On Mar 14, 2011 5:44 PM, <rex.dwyer@syngenta.com<mailto:rex.dwyer@syngenta.com>> wrote:

Tjerk,
This is just a pseudo code outline of what you need to do:

M = matrix(0, number of variables, number of variables)
V = rep(0, number of variables)
N = 0
While (more observations to read) {
  X <- next observation
  V <- V + X
  M <- M + outer(X,X)
  N <- N+1
}
Compute covariance matrix from elements of V,M, and N

You just need to refer to the formula defining covariance.
Outlook seems to think all my variables should be upper case.

HTH
Rex

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