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Mixed-effects models in R using S4 classes and methods with RcppEigen
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lme4/lme4
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- See theNEWS file
- r-sig-mixed-models@r-project.org for questions about
lme4usage and more general mixed model questions; please read the info page, and subscribe, before posting ... (note that the mailing list does not support images or large/non-text attachments) - https://github.com/lme4/lme4/issues for bug, infelicity, and wishlist reporting
- Thelme4 tag on StackOverflow for programming-related or thelme4-nlme tag on CrossValidated for statistics-related questions
- maintainer e-mail only for urgent/private communications
If you choose to supportlme4 development financially, you can contribute to a fund at McMaster University (home institution of one of the developers)here. The form will say that you are donating to the "Global Coding Fund"; this fund is available for use by the developers, under McMaster's research spending rules. We plan to use the funds, as available, to pay students to do maintenance and development work. There is no way to earmark funds or set up a bounty to direct funding toward particular features, but you can e-mail the maintainers and suggest priorities for your donation.
- Efficient for large data sets, using algorithms from theEigenlinear algebra package via theRcppEigeninterface layer.
- Allows arbitrarily many nested and crossed random effects.
- Fits generalized linear mixed models (GLMMs) and nonlinear mixed models (NLMMs) via Laplace approximationor adaptive Gauss-Hermite quadrature; GLMMs allow user-defined families and link functions.
- Incorporates likelihood profiling and parametric bootstrapping.
- From CRAN (stable release 1.+)
- Development version from Github:
library("devtools"); install_github("lme4/lme4",dependencies=TRUE)
(This requiresdevtools >= 1.6.1, and installs the "master" (development) branch.)This approach builds the package 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. Specifybuild_vignettes=FALSE if you have trouble because your system is missing some of theLaTeX/texi2dvi tools.
- Development binaries from r-universe:
install.packages('lme4',repos= c('https://lme4.r-universe.dev', getOption("repos")[["CRAN"]]))
lme4 is developed in a mixture of
- traditional R package building tools, as documented inWriting R Extensions
- NEWS in
inst/NEWS.Rd(not a top-levelNEWS.mdfile) - documentation as
.Rdfiles (notroxygen2, although some functions have internal roxygen-style documentation [not used]) - 'classic' tests in the
tests/directory - some Sweave (
knitr)/Rnw-format vignette, especiallyvignettes/lmer.Rnw
- NEWS in
- 'tidyverse'-style tools, as documented inR Packages (Wickham and Bryan)
testthattests, intests/testthatpkgdownweb site (viapkgdown.extras, extensions to allow PDF vignettes); trigger manual buildshere
- GitHub
- primary development repository
- issues
- testing onGitHub actions (activated by specifying "[run ci]" at the end of a commit message)
- pull requests are welcome, but please open a discussion as an issue first
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Mixed-effects models in R using S4 classes and methods with RcppEigen
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