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lme4 (version 1.0-4)

Linear mixed-effects models using Eigen and S4

Description

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".

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Version

Install

install.packages('lme4')

Monthly Downloads

539,225

Version

1.0-4

License

GPL (>= 2)

Maintainer

Ben Bolker

Last Published

September 21st, 2013

Functions in lme4 (1.0-4)

Paste strength by batch and cask

Classes "lmResp", "glmResp", "nlsResp" and "lmerResp"

Class "merPredD" - a dense predictor reference class

Model-based (Semi-)Parametric Bootstrap for Mixed Models

Make Variance and Correlation Matrices from theta

Predictions from a model at new data values

add information to data based on a fitted model

Breakage angle of chocolate cakes

Contagious bovine pleuropneumonia

Class "golden"

glmFamily-class

Class "glmFamily" - a reference class for family

Verbal Aggression item responses

Data on red grouse ticks from Elston et al. 2001

University Lecture/Instructor Evaluations by Students at ETH

Generator object for the glmFamily class

Getting p-values for fitted models

Create Z, Lambda, Lind, etc.

Generator object for the Nelder-Mead optimizer class.

Is f1 nested within f2?

Extract residual standard error

Class "lmList" of 'lm' Objects on Common Model

NelderMead-class

Class "NelderMead"

Reaction times in a sleep deprivation study

Sparse Gaussian Quadrature grid

densityplot.thpr

densityplot from a mixed-effects profile

List of lm Objects with a Common Model

"Sub[stitute] Bars"

Extract the deviance component list

Generator object for the rePos (random-effects positions) class

profile-methods

Profile method for merMod objects

Determine random-effects expressions from a formula

Refit a model by maximum likelihood criterion

Generator objects for the response classes

Generator object for the golden search optimizer class.

glmer() for Negative Binomial

Extract or Get Generalized Components from a Fitted Mixed Effects Model

Fit Generalized Linear Mixed-Effects Models

Class "merMod" of Fitted Mixed-Effect Models

Generator object for the merPredD class

diagnostic plots for merMod fits

Create an lmerResp, glmResp or nlsResp instance

Univariate Gauss-Hermite quadrature rule

Check characteristics of models

Compute confidence intervals on the parameters of an lme4 fit

Sparse Gauss-Hermite quadrature grids

Control of Mixed Model Fitting

Refit a model by maximum likelihood criterion

Linear, generalized linear, and nonlinear mixed models

Class "rePos"

Manipulate a nonlinear model formula.

residuals.merMod

residuals of merMod objects

Modular functions for mixed model fits

Create a merMod object

Transform to the variance scale

Extract fixed-effects estimates

Fit Linear Mixed-Effects Models

Extract the modes of the random effects

Yield of dyestuff by batch

Extract Variance and Correlation Components

Create a deviance evaluation function from a predictor and a response module

Fit Nonlinear Mixed-Effects Models

Profile pairs plot

Variation in penicillin testing

Omit terms separated by vertical bars in a formula

simulate.merMod

Simulate responses from a merMod object