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How is the covariance factor computed?

Ben Bolker · 2014-07-17T20:18:19Z

Vincent Dorie writes: [snip] > On the other hand, if you were asking where those numbers come from, > it turns out that (at least for linear models) those parameters are > sufficient to define a likelihood wherein the fixed effects and > conditional error term (sigma) are analytically optimized. Since the > goal is a maximum likelihood, or REML, the sigma parameters are then > simply numerically optimized. You can then easily evaluate the mixed > model likelihood at any value

Ben Bolker

Thu, Jul 17, 2014 1:18 PM

Vincent Dorie <vdorie at ...> writes:

 [snip]

... specifically, for this last bit, see the devfun2() function in
https://github.com/lme4/lme4/blob/master/R/profile.R ; there is a
brief description of how this works in the lme4 preprint at
http://arxiv.org/abs/1406.5823 , in the 'profiling' section.  (I
think "... the sigma parameters are then simply numerically optimized"
should be "... the theta parameters ...") [defined in previous para.
as the elements of the Cholesky factorization(s) of the random effects
variance-covariance matri[xc](es) ...]

  Ben Bolker

Thread (8 messages)

Christian Brauner How is the covariance factor computed? Jul 17 Vincent Dorie How is the covariance factor computed? Jul 17 Ben Bolker How is the covariance factor computed? Jul 17 Vincent Dorie How is the covariance factor computed? Jul 17 steve.walker at utoronto.ca How is the covariance factor computed? Jul 17 Christian Brauner How is the covariance factor computed? Jul 18 Ben Bolker How is the covariance factor computed? Jul 18 Christian Brauner How is the covariance factor computed? Jul 19