From: Gabor Grothendieck <ggrothendieck_at_gmail.com>

Date: Thu, 26 Jun 2008 18:48:25 -0400

R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 26 Jun 2008 - 22:52:53 GMT

Date: Thu, 26 Jun 2008 18:48:25 -0400

Not sure if this is sufficient but nearcor in the sfsmisc package will find the nearest correlation matrix to a given matrix.

On Thu, Jun 26, 2008 at 12:11 PM, Mizanur Khondoker
<Mizanur.Khondoker_at_ed.ac.uk> wrote:

> Dear list,

*>
**> I am trying to use the 'mvrnorm' function from the MASS package for
**> simulating multivariate Gaussian data with given covariance matrix.
**> The diagonal elements of my covariance matrix should be the same,
**> i.e., all variables have the same marginal variance. Also all
**> correlations between all pair of variables should be identical, but
**> could be any value in [-1,1]. The problem I am having is that the
**> matrix I create is not always positive definite (and hence mvrnorm
**> fails).
**>
**> Is there any simple way of constructing covariance matrix of the above
**> structure (equal variance, same pairwise correlation from [-1, 1])
**> that will always be positive definite?
**> I have noticed that covraince matrices created using the following COV
**> function are positive definite for -0.5 < r <1. However, for r <
**> -0.5, the matrix is not positive definite.
**> Does anyone have any idea why this is the case? For my simualtion, I
**> need to generate multivariate data for the whole range of r, [-1, 1]
**> for a give value of sd.
**>
**> Any help/ suggestion would be greatly appreciated.
**>
**> Examples
**> ########
**> COV<-function (p = 3, sd = 1, r= 0.5){
**> cov <- diag(sd^2, ncol=p, nrow=p)
**> for (i in 1:p) {
**> for (j in 1:p) {
**> if (i != j) {
**> cov[i, j] <- r * sd*sd
**> }
**> }
**> }
**> cov
**> }
**>
**>> library(MASS)
**>> ### Simualte multivarite gaussin data (works OK)
**>> Sigma<-COV(p = 3, sd = 2, r= 0.5)
**>> mu<-1:3
**>> mvrnorm(5, mu=mu, Sigma=Sigma)
**> [,1] [,2] [,3]
**> [1,] 1.2979984 1.843248 4.460891
**> [2,] 2.1061054 1.457201 3.774833
**> [3,] 2.1578538 2.761939 4.589977
**> [4,] 0.8775056 4.240710 2.203712
**> [5,] 0.2698180 2.075759 2.869573
**>>
**>> ### Simualte multivarite gaussin data ( gives Error)
**>> Sigma<-COV(p = 3, sd = 2, r= -0.6)
**>> mu<-1:3
**>> mvrnorm(5, mu=mu, Sigma=Sigma)
**> Error in mvrnorm(5, mu = mu, Sigma = Sigma) :
**> 'Sigma' is not positive definite
**>
**> --
**> Mizanur Khondoker
**> Division of Pathway Medicine (DPM)
**> The University of Edinburgh Medical School
**> The Chancellor's Building
**> 49 Little France Crescent
**> Edinburgh EH16 4SB
**> United Kingdom
**>
**> Tel: +44 (0) 131 242 6287
**> Fax: +44 (0) 131 242 6244
**> http://www.pathwaymedicine.ed.ac.uk/
**>
**> ______________________________________________
**> R-help_at_r-project.org mailing list
**> https://stat.ethz.ch/mailman/listinfo/r-help
**> PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
**> and provide commented, minimal, self-contained, reproducible code.
**>
*

R-help_at_r-project.org mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code. Received on Thu 26 Jun 2008 - 22:52:53 GMT

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