lme4: Linear Mixed-Effects Models using 'Eigen' and S4

Fit linear and generalized linear mixed-effects models. The models and their components are represented using S4 classes and methods. The core computational algorithms are implemented using the 'Eigen' C++ library for numerical linear algebra and 'RcppEigen' "glue".

Version: 1.1-12
Depends: R (≥ 3.0.2), Matrix (≥ 1.1.1), methods, stats
Imports: graphics, grid, splines, utils, parallel, MASS, lattice, nlme (≥ 3.1-123), minqa (≥ 1.1.15), nloptr (≥ 1.0.4)
LinkingTo: Rcpp (≥ 0.10.5), RcppEigen
Suggests: knitr, boot, PKPDmodels, MEMSS, testthat (≥ 0.8.1), ggplot2, mlmRev, optimx (≥ 2013.8.6), gamm4, pbkrtest, HSAUR2, numDeriv
Published: 2016-04-16
Author: Douglas Bates [aut], Martin Maechler [aut], Ben Bolker [aut, cre], Steven Walker [aut], Rune Haubo Bojesen Christensen [ctb], Henrik Singmann [ctb], Bin Dai [ctb], Gabor Grothendieck [ctb], Peter Green [ctb]
Maintainer: Ben Bolker <bbolker+lme4 at gmail.com>
Contact: LME4 Authors <lme4-authors@lists.r-forge.r-project.org>
BugReports: https://github.com/lme4/lme4/issues
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/lme4/lme4/ http://lme4.r-forge.r-project.org/
NeedsCompilation: yes
Citation: lme4 citation info
Materials: NEWS ChangeLog
In views: Bayesian, Econometrics, Environmetrics, OfficialStatistics, Psychometrics, SocialSciences, SpatioTemporal
CRAN checks: lme4 results

Downloads:

Reference manual: lme4.pdf
Vignettes: lmer Performance Tips
Fitting Linear Mixed-Effects Models using lme4
PLS vs GLS for LMMs
Computational Methods
Package source: lme4_1.1-12.tar.gz
Windows binaries: r-devel: lme4_1.1-12.zip, r-release: lme4_1.1-12.zip, r-oldrel: lme4_1.1-12.zip
OS X Mavericks binaries: r-release: lme4_1.1-12.tgz, r-oldrel: lme4_1.1-12.tgz
Old sources: lme4 archive

Reverse dependencies:

Reverse depends: afex, agRee, aods3, ArfimaMLM, arm, bapred, Bayesthresh, BBRecapture, blme, BradleyTerry2, cAIC4, carcass, CLME, difR, fishmethods, fullfact, gamm4, GLMMRR, GWAF, iccbeta, influence.ME, JAGUAR, JointModel, lmerTest, longpower, marked, MEMSS, merTools, Metatron, mixAK, MixRF, mlma, mlmRev, neuropsychology, nonrandom, pbkrtest, pedigreemm, predictmeans, prLogistic, robustlmm, simr
Reverse imports: ARTool, blmeco, brms, climwin, clusterPower, DHARMa, effects, ez, faraway, glmmsr, inferference, lmem.gwaser, lmem.qtler, LMERConvenienceFunctions, lmSupport, LSAmitR, mbest, mediation, metaplus, miceadds, mixlm, MixMAP, mlVAR, multiDimBio, MultiRR, MXM, omics, pamm, PBImisc, piecewiseSEM, powerbydesign, R2STATS, refund, refund.shiny, reproducer, RLRsim, rockchalk, rptR, RRreg, rstanarm, RVAideMemoire, RVFam, SensMixed, sjmisc, sjPlot, sjstats, SoyNAM, spacom, SPreFuGED, squid, StroupGLMM, Surrogate, TcGSA, tnam, VCA, VetResearchLMM
Reverse suggests: agridat, AICcmodavg, ANOM, aod, AzureML, BayesFactor, benchmark, BIFIEsurvey, broom, car, catdata, DAAG, dlnm, doBy, Epi, expp, eyetrackingR, flexmix, glmulti, gmodels, hamlet, HLMdiag, hnp, HSAUR, HSAUR2, HSAUR3, irtrees, KFAS, kulife, kyotil, languageR, lava, likelihoodAsy, lmeresampler, lsmeans, lucid, MESS, meta, metafor, MethComp, mice, mitml, multcomp, MuMIn, mztwinreg, NAM, NanoStringNorm, OpenMx, ordinal, pan, pez, phia, phmm, purge, R2admb, r2glmm, RcmdrPlugin.NMBU, SASmixed, spaMM, SPOT, texreg, TripleR
Reverse enhances: memisc, papeR, stargazer

Linking:

Please use the canonical form https://CRAN.R-project.org/package=lme4 to link to this page.