Generalized Linear Mixed Models using Template Model Builder
Get theta parameterisation of a covariance structure
support methods for parametric bootstrapping
Calculate confidence intervals
diagnose model problems
Adjust a model matrix When not rank deficient, do nothing. When rank d...
Check for identifiability of fixed effects matrices X, Xzi, Xdisp. Whe...
collapse duplicated observations
Downstream methods
truncated distributions
Retrieve family-specific parameters
Optimize TMB models and package results, modularly
Extract fixed-effects estimates
Format the 'VarCorr' Matrix of Random Effects
Extract the formula of a glmmTMB object
translate vector of correlation parameters to correlation values
List model options that glmmTMB knows about
Get Grouping Variable
Extract or Get Generalize Components from a Fitted Mixed Effects Model
Calculate random effect structure Calculates number of random effects,...
Create X and random effect terms from formula
Methods for extracting developer-level information from glmmTMB mode...
Fit Models with TMB
Control parameters for glmmTMB optimization
conditionally update glmmTMB object fitted with an old TMB version
Set map values for theta to be fixed (NA) for propto
Extract info from formulas, reTrms, etc., format for TMB
Family functions for glmmTMB
Factor with numeric interpretable levels.
Check OpenMP status
prediction
Printing The Variance and Correlation Parameters of a glmmTMB
use of priors in glmmTMB
Compute likelihood profiles for a fitted model
Extract Random Effects
Objects exported from other packages
Reinstalling binary dependencies
Compute residuals for a glmmTMB object
helper function to modify simulation settings for random effects
Extract residual standard deviation or dispersion parameter
Simulate from covariate/metadata in the absence of a real data set (EX...
Simulate from a glmmTMB fitted model
Change starting parameters, either by residual method or by user input...
Extract variance and correlation components
Calculate Variance-Covariance Matrix for a Fitted glmmTMB model
Extract weights from a glmmTMB object
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.