I am trying to estimate the sparse inverse covariance matrix of my gaussian graphical model. I installed the `glasso`

package in R and tried out some examples.

After that I ran the `glasso`

software on my own data. So I fed it my empirical covariance matrix. However, it seems to get stuck and doesn't give me the results. So I was wondering if I was running the software incorrectly.

I followed this manual: http://cran.r-project.org/web/packages/glasso/glasso.pdf

So if `S`

is my empirical covariance matrix. I just ran the following:

`a <- glasso(S, rho=.01, trace=TRUE) # outer loop, m = 1 # outer loop, m = 2 `

After the above, it gets stuck.

I am attaching my empirical covariance matrix as well which I feed to the software.

http://rapidshare.com/files/141198734/emp_covariance_matrix.mat

Any guidance will be much appreciated.

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#### Best Answer

Did you standardized data before estimation of covariance matrix? Standardization is necessary before you run glasso, though there may be exceptions ( however, I am not sure about those ocassions). Other option may be estimate covarience matrix and then transform it into correlation matrix. Then run glasso and see the result. Hope it works.

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