Hi.
I have a data matrix of size 3072x1910. I can compute a standard 1910x1910
covariance matrix for this, and it comes out positive definite. I wanted to
compute a robust covariance matrix with cov.nnve (in the covRobust library).
It failed with the following error message:
Error in while (abs(loglik.new - loglik.old)/(1 + abs(loglik.new)) >
convergence) { :
missing value where TRUE/FALSE needed
In addition: Warning message:
value out of range in 'gammafn'
So I'm seeking advice / assistance. I have also tried covRob (in the robust
library), which has some different methods for robust covariance estimation,
but it runs out of memory (I usually have about 1.5Gb available).
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