lme4 v1.0-4

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by Ben Bolker

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".

Functions in lme4

Name Description
Pastes Paste strength by batch and cask
lmResp-class Classes "lmResp", "glmResp", "nlsResp" and "lmerResp"
merPredD-class Class "merPredD" - a dense predictor reference class
bootMer Model-based (Semi-)Parametric Bootstrap for Mixed Models
mkVarCorr Make Variance and Correlation Matrices from theta
predict.merMod Predictions from a model at new data values
fortify add information to data based on a fitted model
cake Breakage angle of chocolate cakes
cbpp Contagious bovine pleuropneumonia
golden-class Class "golden"
glmFamily-class Class "glmFamily" - a reference class for family
VerbAgg Verbal Aggression item responses
grouseticks Data on red grouse ticks from Elston et al. 2001
InstEval University Lecture/Instructor Evaluations by Students at ETH
glmFamily Generator object for the glmFamily class
pvalues Getting p-values for fitted models
mkReTrms Create Z, Lambda, Lind, etc.
NelderMead Generator object for the Nelder-Mead optimizer class.
isNested Is f1 nested within f2?
sigma Extract residual standard error
lmList-class Class "lmList" of 'lm' Objects on Common Model
NelderMead-class Class "NelderMead"
sleepstudy Reaction times in a sleep deprivation study
GQdk Sparse Gaussian Quadrature grid
densityplot.thpr densityplot from a mixed-effects profile
lmList List of lm Objects with a Common Model
subbars "Sub[stitute] Bars"
devcomp Extract the deviance component list
rePos Generator object for the rePos (random-effects positions) class
profile-methods Profile method for merMod objects
findbars Determine random-effects expressions from a formula
refitML Refit a model by maximum likelihood criterion
lmResp Generator objects for the response classes
golden Generator object for the golden search optimizer class.
glmer.nb glmer() for Negative Binomial
getME Extract or Get Generalized Components from a Fitted Mixed Effects Model
glmer Fit Generalized Linear Mixed-Effects Models
merMod-class Class "merMod" of Fitted Mixed-Effect Models
merPredD Generator object for the merPredD class
plot.merMod diagnostic plots for merMod fits
mkRespMod Create an lmerResp, glmResp or nlsResp instance
GHrule Univariate Gauss-Hermite quadrature rule
isREML Check characteristics of models
confint.merMod Compute confidence intervals on the parameters of an lme4 fit
GQN Sparse Gauss-Hermite quadrature grids
lmerControl Control of Mixed Model Fitting
refit Refit a model by maximum likelihood criterion
lme4-package Linear, generalized linear, and nonlinear mixed models
rePos-class Class "rePos"
nlformula Manipulate a nonlinear model formula.
residuals.merMod residuals of merMod objects
modular Modular functions for mixed model fits
mkMerMod Create a merMod object
varianceProf Transform to the variance scale
fixef Extract fixed-effects estimates
lmer Fit Linear Mixed-Effects Models
ranef Extract the modes of the random effects
Dyestuff Yield of dyestuff by batch
VarCorr Extract Variance and Correlation Components
mkdevfun Create a deviance evaluation function from a predictor and a response module
nlmer Fit Nonlinear Mixed-Effects Models
splom.thpr Profile pairs plot
Penicillin Variation in penicillin testing
nobars Omit terms separated by vertical bars in a formula
simulate.merMod Simulate responses from a merMod object
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Details

Date 2013-09-08
Contact LME4 Authors
LinkingTo Rcpp, RcppEigen
LazyData yes
License GPL (>= 2)
URL http://lme4.r-forge.r-project.org/
Collate 'AllClass.R' 'AllGeneric.R' 'GHrule.R' 'lmer.R' 'lmList.R' 'profile.R' 'sparsegrid.R' 'utilities.R' 'optimizer.R' 'predict.R' 'bootMer.R' 'nbinom.R' 'mcmcsamp.R' 'plot.R' 'vcconv.R' 'modular.R' 'hooks.r' 'lmerControl.R'
BuildVignettes yes
Packaged 2013-09-21 07:50:15 UTC; ripley
NeedsCompilation yes
Repository CRAN
Date/Publication 2013-09-21 10:00:40

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