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 (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.)
lme4.0 is a maintained version of lme4 back compatible to CRAN versions of lme4 0.99xy, mainly for the purpose of reproducible research and data analysis which was done with 0.99xy versions of lme4.
getME(<mod>, "..") which is compatible (as much as sensibly possible) to current
lme4s version of
- It currently resides on R-forge, and you can install it with