Carlo Fezzi (ENV <C.Fezzi <at> uea.ac.uk> writes: > > Dear all, > > I am writing an R code to fit a Bayesian mixed logit (BML) via MCMC / MH algorithms following Train (2009, ch. 12). > > Unfortunately, after many draws the covariance matrix > of the correlated random parameters tend to become > a matrix with almost perfect correlation, so I think > there is a bug in the code I wrote but I do not seem to be > able to find it.. dull I know. > > Has anybody written a code for BML with R and would like to share it with me or even take a quick look at my code? I > would be extremely grateful for any help.
(1) maybe better at r-sig-mixed-mod...@r-project.org (2) are you trying this on real, or on simulated data? The collapse of the covariance matrix in this way is a very common symptom of overfitting/underidentification in mixed models. I wouldn't say it necessarily constitutes a bug in your code. In principle you should be able to get an uncorrelated answer if you use a big enough, sufficiently well-behaved simulated data set, but not necessarily for real data ... (3) have you tried the MCMCglmm package, which is a very fast and flexible MCMC-based approach to GLMMs? ______________________________________________ R-help@r-project.org 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.
