Package index • glmmTMB

All functions
`Owls`	Begging by Owl Nestlings
`Salamanders`	Repeated counts of salamanders in streams
`as.theta.vcov()`	Get theta parameterisation of a covariance structure
`isLMM(<glmmTMB>)` `refit(<glmmTMB>)`	support methods for parametric bootstrapping
`bread(<glmmTMB>)`	Bread Matrix for Sandwich Estimator
`confint(<glmmTMB>)`	Calculate confidence intervals
`diagnose()`	diagnose model problems
`dof_KR()` `dof_satt()`	compute denominator degrees-of-freedom approximations
`Anova.glmmTMB()` `Effect.glmmTMB()`	Downstream methods
`dtruncated_nbinom2()` `dtruncated_poisson()` `dtruncated_nbinom1()`	truncated distributions
`epil2`	Seizure Counts for Epileptics - Extended
`estfun(<glmmTMB>)`	Extract Empirical Estimating Functions
`family_params()`	Retrieve family-specific parameters
`fitTMB()` `finalizeTMB()`	Optimize TMB models and package results, modularly
`fixef(<glmmTMB>)`	Extract fixed-effects estimates
`formatVC()`	Format the 'VarCorr' Matrix of Random Effects
`format_sdvar()` `format_corr()` `get_sd()`	format columns corresponding to std. dev. and/or variance
`formula(<glmmTMB>)`	Extract the formula of a glmmTMB object
`getCapabilities()`	List model options that glmmTMB knows about
`getGroups(<glmmTMB>)`	Extract Grouping Factors from an Object
`getME(<glmmTMB>)`	Extract or Get Generalize Components from a Fitted Mixed Effects Model
`getReStruc()`	Calculate random effect structure Calculates number of random effects, number of parameters, block size and number of blocks. Mostly for internal use.
`getXReTrms()`	Create X and random effect terms from formula
`get_autopar()`	retrieve current value of TMB autopar setting
`get_cor()` `put_cor()`	transform correlation parameters to and from glmmTMB parameterization
`glmmTMB()`	Fit Models with TMB
`glmmTMBControl()`	Control parameters for glmmTMB optimization
`terms(<glmmTMB>)` `model.matrix(<glmmTMB>)`	Methods for extracting developer-level information from `glmmTMB` models
`up2date()` `gt_load()`	conditionally update glmmTMB object fitted with an old TMB version
`map.theta.propto()`	Set map values for theta to be fixed (NA) for propto
`meatHC()`	Simple Cluster Based Meat Matrix Estimator
`nbinom2()` `nbinom1()` `nbinom12()` `compois()` `truncated_compois()` `genpois()` `truncated_genpois()` `truncated_poisson()` `truncated_nbinom2()` `truncated_nbinom1()` `beta_family()` `betabinomial()` `tweedie()` `skewnormal()` `lognormal()` `ziGamma()` `t_family()` `ordbeta()` `bell()`	Family functions for glmmTMB
`numFactor()` `parseNumLevels()`	Factor with numeric interpretable levels.
`omp_check()`	Check OpenMP status
`predict(<glmmTMB>)`	prediction
`print(<VarCorr.glmmTMB>)`	Printing The Variance and Correlation Parameters of a `glmmTMB`
`priors`	use of priors in glmmTMB
`profile(<glmmTMB>)` `confint(<profile.glmmTMB>)`	Compute likelihood profiles for a fitted model
`ranef(<glmmTMB>)` `as.data.frame(<ranef.glmmTMB>)` `coef(<glmmTMB>)`	Extract Random Effects
`reinstalling`	Reinstalling binary dependencies
`residuals(<glmmTMB>)` `deviance(<glmmTMB>)`	Compute residuals for a glmmTMB object
`sandwich()`	Sandwich Estimator based on Bread and Meat Matrices
`set_simcodes()`	helper function to modify simulation settings for random effects
`sigma(<glmmTMB>)`	Extract residual standard deviation or dispersion parameter
`simulate(<glmmTMB>)`	Simulate from a glmmTMB fitted model
`simulate_new()`	Simulate from covariate/metadata in the absence of a real data set (EXPERIMENTAL)
`spider_long`	Spider data from CANOCO, long format
`summary(<glmmTMB>)`	summary for glmmTMB fits
`vcov(<glmmTMB>)`	Calculate Variance-Covariance Matrix for a Fitted glmmTMB model
`vcovHC(<glmmTMB>)`	Cluster Robust Variance-Covariance Matrix Estimator
`weights(<glmmTMB>)`	Extract weights from a glmmTMB object

Reference

All functions