A new version, 0.65-1, of glmmML is now on CRAN. It is a major rewrite of the inner structures, so frequent updates (bug fixes) may be expected for some time.
News: * The Laplace and adaptive Gauss-Hermite approximations to the log likelihood function are fully implemented. The Laplace method is made the default. It should give results you can compare to the results from 'lmer' (for the models that glmmML can handle). * Binomial responses can now be represented as a two-column matrix with No. of successes and No. of failures, respectively, as in glm. * New functions: 'ghq' for calculating the constants used in the Gauss-Hermite quadrature. 'extractAIC.glmmML', which makes it possible to use functions like 'dropterm' (MASS) on glmmML fits. * There are three choices of distribution for the random effects: 'gaussian' (default), 'logistic', and 'cauchy'. * The 'conditional' bootstrap is removed, so the only choice now is the parametric bootstrap. * The 'posterior.means' are no longer calculated, leaving only the 'posterior.modes' as 'predictions' of the random effects. As usual, feedback is more than welcome! Göran _______________________________________________ R-packages mailing list [EMAIL PROTECTED] https://stat.ethz.ch/mailman/listinfo/r-packages ______________________________________________ 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 and provide commented, minimal, self-contained, reproducible code.