- 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.- Notably,
lme4.0
featuresgetME(<mod>, "..")
which is compatible (as much as sensibly possible) to currentlme4
s version ofgetME()
. - It currently resides on R-forge, and you can install it with
install.packages("lme4.0",
repos=c("http://lme4.r-forge.r-project.org/repos",
getOption("repos")[["CRAN"]]))