[R] sem: S is numerically singular: expect problems
jfox at mcmaster.ca
Tue Apr 9 15:24:30 CEST 2013
Dear Amarnath Bose,
S is the observed-variables covariance or moment matrix and thus doesn't
really have to do with the model that you're fitting, nor with the sem
software per se; rather, S is computed directly from the data.
It's not possible without the data to know why S is numerically singular.
The message you quote suggests three reasons, but these aren't exhaustive.
Investigating the eigenstructure or SVD of S or the data matrix might help
-- e.g., through a principal components analysis.
I hope this helps,
Senator McMaster Professor of Social Statistics
Department of Sociology
Hamilton, Ontario, Canada
> -----Original Message-----
> From: r-help-bounces at r-project.org [mailto:r-help-bounces at r-
> project.org] On Behalf Of Amarnath Bose
> Sent: Tuesday, April 09, 2013 8:22 AM
> To: r-help at r-project.org
> Subject: [R] sem: S is numerically singular: expect problems
> Dear Users,
> I am a new user of the sem package.
> I have a model that is being flagged by sem as "S is numerically
> expect problems"
> I have checked John Fox's response to a similar problem. Obviously the
> variance-covariance matrix is singular, but none of the possible
> seems to hold in my case.
> Any leads how I could get the model to work?
> from Prof. John Fox
> That seems to me a reasonably informative error message: The
> observed-variable covariance matrix is singular. This could happen,
> e.g., if
> two observed variables are perfectly correlated, if an observed
> variable had
> 0 variance, or if there were more observed variables than observations.
> *Amarnath Bose*
> * **Associate Professor *
> *Decision Sciences Department*
> *Birla Institute of Management Technology
> Tel: +91 120 2323001 - 10 Ext.: 398
> Cell: +91 9873179813
> [[alternative HTML version deleted]]
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