andreaphsz / lme4

Mixed-effects models in R using S4 classes and methods with RcppEigen

lme4: Mixed-effects models in R.

Features

• Efficient for large data sets, using algorithms from the Eigen linear algebra package via the RcppEigen interface layer.
• Allows arbitrarily many nested and crossed random effects.
• Fits generalized linear mixed models (GLMMs) and nonlinear mixed models (NLMMs) via Laplace approximation or adaptive Gauss-Hermite quadrature; GLMMs allow user-defined families and link functions.
• Incorporates likelihood profiling and parametric bootstrapping.

Installation

• From CRAN (note stable version 0.999999-2 will soon be superseded by stable release 1.0.+)
• Nearly up-to-date development binaries from lme4 r-forge repository:

install.packages("lme4",
   repos=c("http://lme4.r-forge.r-project.org/repos",
          getOption("repos")["CRAN"]))

• Development version from Github:

library("devtools"); install_github("lme4",user="lme4")

(These commands install the "master" (development) branch; if you want the release branch from Github add ref="release" to the install_github() call. The install_github() approach requires that you build from source, i.e. make and compilers must be installed on your system -- see the R FAQ for your operating system; you may also need to install dependencies manually.)