# glmmTMB v0.2.3

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## Generalized Linear Mixed Models using Template Model Builder

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.

## Functions in glmmTMB

 Name Description 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 No Results!

## Vignettes of glmmTMB

 Name InstEvalTimings.rda contraceptionTimings.rda covstruct.rmd glmmTMB.Rnw glmmTMB.bib mcmc.rmd miscEx.rmd model_evaluation.rmd sim.rmd timingContraception.R timingFuns.R timingInstEval.R troubleshooting.rmd No Results!