Re: [R] computing var-covar matrix with much missing data

One option is the nearPD function in the Matrix package. Other options include robust estimation of the covariance matrix. You should Google this. It's been discussed before. Kevin Wright On Mon, Jan 31, 2011 at 11:30 AM, Mike Miller > wrote: > Is there an R function for computing a varianc

Re: [R] computing var-covar matrix with much missing data

On Mon, Jan 31, 2011 at 9:30 AM, Mike Miller wrote: > Is there an R function for computing a variance-covariance matrix that > guarantees that it will have no negative eigenvalues?  In my case, there is > a *lot* of missing data, especially for a subset of variables.  I think my > tactic will be t

[R] computing var-covar matrix with much missing data

Is there an R function for computing a variance-covariance matrix that guarantees that it will have no negative eigenvalues? In my case, there is a *lot* of missing data, especially for a subset of variables. I think my tactic will be to compute cor(x, use="pairwise.complete.obs") and then pr