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glmmTMB (version 0.2.3)

Generalized Linear Mixed Models using Template Model Builder

Description

Fit linear and generalized linear mixed models with various extensions, including zero-inflation. The models are fitted using maximum likelihood estimation via 'TMB' (Template Model Builder). Random effects are assumed to be Gaussian on the scale of the linear predictor and are integrated out using the Laplace approximation. Gradients are calculated using automatic differentiation.

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Version

Install

install.packages('glmmTMB')

Monthly Downloads

35,703

Version

0.2.3

License

AGPL-3

Maintainer

Mollie Brooks

Last Published

January 11th, 2019

Functions in glmmTMB (0.2.3)

simulate.glmmTMB

Simulate from a glmmTMB fitted model
getME.glmmTMB

Extract or Get Generalize Components from a Fitted Mixed Effects Model
nbinom2

Family functions for glmmTMB
getGrpVar

Get Grouping Variable
numFactor

Factor with numeric interpretable levels.
print.VarCorr.glmmTMB

Printing The Variance and Correlation Parameters of a glmmTMB
predict.glmmTMB

prediction
findReTrmClasses

list of specials -- taken from enum.R
fixef

Extract fixed-effects estimates
inForm

test formula: does it contain a particular element?
formatVC

Format the 'VarCorr' Matrix of Random Effects
profile.glmmTMB

Compute likelihood profiles for a fitted model
ranef.glmmTMB

Extract Random Effects
addForm

Combine right-hand sides of an arbitrary number of formulas
tmbroot

Compute likelihood profile confidence intervals of a TMB object by root-finding (generalized from TMB::tmbprofile)
getCapabilities

List model options that glmmTMB knows about
formula.glmmTMB

Extract the formula of a glmmTMB object
.collectDuplicates

collapse duplicated observations
vcov.glmmTMB

Calculate Variance-Covariance Matrix for a Fitted glmmTMB model
getReStruc

Calculate random effect structure Calculates number of random effects, number of parameters, blocksize and number of blocks. Mostly for internal use.
get_cor

translate vector of correlation parameters to correlation values, following the definition at http://kaskr.github.io/adcomp/classUNSTRUCTURED__CORR__t.html: if \(L\) is the lower-triangular matrix with 1 on the diagonal and the correlation parameters in the lower triangle, then the correlation matrix is defined as \(\Sigma = D^{-1/2} L L^\top D^{-1/2}\), where \(D = \textrm{diag}(L L^\top)\). For a single correlation parameter \(\theta_0\), this works out to \(\rho = \theta_0/\sqrt{1+\theta_0^2}\).
glmmTMB

Fit models with TMB
residuals.glmmTMB

Compute residuals for a glmmTMB object
glmmTMBControl

Control parameters for glmmTMB optimization
getXReTrms

Create X and random effect terms from formula
sigma.glmmTMB

Extract residual standard deviation or dispersion parameter
mkTMBStruc

Extract info from formulas, reTrms, etc., format for TMB
confint.glmmTMB

Calculate confidence intervals
Owls

Begging by Owl Nestlings
Salamanders

Repeated counts of salamanders in streams
Anova.glmmTMB

Downstream methods for glmmTMB objects
epil2

Seizure Counts for Epileptics - Extended
expandAllGrpVar

expand interactions/combinations of grouping variables
VarCorr.glmmTMB

Extract variance and correlation components
fbx

(f)ind (b)ars e(x)tended: recursive
isLMM.glmmTMB

support methods for parametric bootstrapping