Hi Liliana,
how about the following:
p <- 10 # assume a 10-dim normal H <- abs(outer(1:p, 1:p, "-")) # I think you |i-j|
library(mvtnorm) fn <- function(rho, dat, H) -sum(log(dmvnorm(dat, sigma=rho^H)))
optimize(fn, c(-1,1), dat=rmvnorm(1000, sigma=0.5^H), H=H)
I hope it helps.
Best, Dimitris
---- Dimitris Rizopoulos Ph.D. Student Biostatistical Centre School of Public Health Catholic University of Leuven
Address: Kapucijnenvoer 35, Leuven, Belgium Tel: +32/16/336899 Fax: +32/16/337015 Web: http://www.med.kuleuven.ac.be/biostat http://www.student.kuleuven.ac.be/~m0390867/dimitris.htm
----- Original Message ----- From: "Liliana Forzani" <[EMAIL PROTECTED]>
Cc: "R-News" <[EMAIL PROTECTED]>
Sent: Wednesday, December 08, 2004 3:32 PM
Subject: [R] correlation matrix o
Hi, I have data normal with mean 0, I was wondering how to get (using R)
the best r such that the correlation matrix of my data has the form
{r^(i-j)} where (i,j) indicate row and columm respectivly. Thanks. Liliana
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