Institute of Mathematics


Modul:   STA671  Kolloquium über anwendungsorientierte Statistik

Recent Computational Advances for Mixed-effects Modeling

Prof. Dr. Douglas Bates talk

Date: 25.09.18  Time: 15.15 - 16.15  Room: ETH HG G 19.1

The lme4 package for R is widely used (google scholar claims more than 10,000 citations of our 2015 J. Stat. Soft. paper on it) but many of its users still encounter convergence problems or long delays in fitting complex models to large data sets. Several years ago I became interested in using the Julia programming language ( to reimplement and improve the algorithms in lme4. The good news is that this project has been, I think, successful in that the MixedModels package provides fast and reliable fitting of both linear mixed-effects models and generalized linear mixed-effects models. However, not everyone is willing to switch to a new programming language to be able to take advantage of one package that may only be a small part of their usage. Julia does not yet have the scope and level of expertise for data analysis, manipulation and visualization that R does. It becomes important to provide the ability to communicate between the languages and, in particular, to exchange data between them. I will discuss some of the capabilities in Julia that make the development of the MixedModels package feasible and some of the mechanisms for communications between the languages.