From: Douglas Bates <bates_at_stat.wisc.edu>

Date: Fri 20 May 2005 - 00:21:43 EST

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri May 20 00:28:15 2005

Date: Fri 20 May 2005 - 00:21:43 EST

PIERRE-JOSEPH tessa wrote:

> On a real data set, running the lme function, I get

*> parameters estimation and a log-likelihood value.
**> Nevertheless, the variance-covariance matrix in this
**> case had a determinant close to zero. So, I could not
**> calculate the log-likelihood myself with the classical
**> expression.
**> What is the calculus made in lme?
*

The evaluation of the log-likelihood used in lme is documented in chapter 2 of Pinheiro and Bates (Springer, 2000). The calculation used in lmer from the lme4 package is somewhat different. If you wish I can send you off-list copies of slides from a presentation that explains that calculation.

I'm not sure which variance-covariance matrix you are referring to but it is the case that the ML or REML estimates of the variance-covariance matrix of the random effects can be singular, a fact that is often ignored in the analysis of data with such models.

R-help@stat.math.ethz.ch mailing list

https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html Received on Fri May 20 00:28:15 2005

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