lme4: Mixed-effects models in R.
- 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.
- From CRAN (note stable version 0.999999-2 will soon be superseded by stable release 1.0.+)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") (The last 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.)