[R] [R-pkgs] glmmML updated

From: Göran Broström <goran.brostrom_at_gmail.com>
Date: Thu 13 Jul 2006 - 02:59:08 EST

I have uploaded a new version (0.30-2) of glmmML to CRAN today.

This is a rather extensive upgrade, mostly internal. Adaptive Gauss-Hermite quadrature (GHQ) is now used for the evaluation of the integrals in the log likelihood function. The user can choose the number of points (default is 16), I _think_ that choosing 1 point will result in a Laplace approximation. The integrals in the score and hessian are evaluated by the QUADPACK function 'Rdqagi' which is the C code behind the R function 'integrate'. This specific combination of the two methods seems to work best. (I often get _exactly_ (up to seven digits) the same value with the two methods, but in some extreme cases one may fail and not the other.)

New components in the output from 'glmmML' are 'posterior.means' and posterior.modes'. The modes are found by using 'vmmin' (behind R's 'optim') on the integrands in the GHQ, the means by numerical integration. Usually, they do not differ much.

A special problem is situations where the random effects variance is very small or zero. I may happen that glmmML is unable to get the likelihood value above the value given by 'glm' on the corresponding model with no clustering. In such a case zero variance is reported, with a standard error that is NA. A warning is also given. If a test of the hypothesis that sigma = 0 is on the wish list, a p-value can be estimated by bootstrapping, see the input parameter 'boot'. The only option now is a parametric bootstrap; I have removed the 'conditional' approach.

As usual, comments, and error and bug reports are welcome.


Göran Broström

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Received on Sat Jul 15 03:05:58 2006

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