MCMCglmm
[This article was first published on Shige's Research Blog, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
This R packages estimates Generalised Linear Mixed Models via MCMC. It provides a number of random error distributions and can be used for multivariate multilevel models (simultaneous equation model).Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
I will do some tests and compare the results to other packages.
This package has the potential to become the ideal modeling tool for multilevel and multiprocess analysis for Bayesians, just as aML and Sabre for non-Bayesians. I have been hoping the new JAGS can have much improved performance with similar models, but I don’t know when the new version (2.0) will be out. I will be interesting to conduct a benchmark test between aML, Sabre, GLLAMM, MCMCglmm, WinBUGS, and JAGS on some complicated multilevel multiprocess statistical models.
Unlike aML and Sabre, MCMCglmm seems to be under active development.
To leave a comment for the author, please follow the link and comment on their blog: Shige's Research Blog.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.