Package index • drmTMB

Package

drmTMB-package: drmTMB: Distributional Regression Models Using TMB

Model specification

Formula constructors, family objects, and status-marked model syntax.

drm_formula() bf(): Build a drmTMB formula object
meta_V(): Known sampling covariance marker
mi(): Missing-predictor model marker
impute_model(): Define a missing-predictor model
meta_vcov_bivariate(): Build paired bivariate sampling covariance
beta(): Beta response family
zero_one_beta(): Zero-one beta response family
beta_binomial(): Beta-binomial response family
cumulative_logit(): Cumulative logit ordinal response family
categorical(): Unordered categorical missing-predictor family
student(): Student-t response family
skew_normal(): Skew-normal response family
lognormal(): Lognormal response family
tweedie(): Tweedie response family
nbinom2(): Negative binomial 2 response family
truncated_nbinom2(): Zero-truncated negative binomial 2 response family
biv_gaussian(): Bivariate Gaussian response family
biv_lognormal(): Bivariate lognormal response family
biv_student(): Bivariate Student-t response family
latent_normal(): Construct a latent-normal association kernel

Structured-effect markers

Status-marked random-effect scale, structured covariance, and latent-correlation syntax; each reference page separates fitted routes from planned neighbours.

random_effect_scale_formulas sd sd1 sd2 sd_phylo sd_phylo1 sd_phylo2: Random-effect scale formula syntax
animal(): Animal-model structured-effect marker
phylo(): Phylogenetic structured-effect marker
phylo_interaction(): Bipartite phylogenetic interaction marker
spatial(): Spatial structured-effect marker
spatial_coords(): Transform longitude and latitude to planar spatial coordinates
make_mesh(): Construct a fixed-kappa SPDE mesh
relmat(): User-supplied relatedness structured-effect marker
corpair(): Latent random-effect correlation formula marker

Deprecated marker internals

Older deprecated formula markers kept out of the main reader path.

meta_known_V(): Deprecated known sampling covariance marker
gr(): Deprecated legacy known-covariance group effect marker

Model fitting and post-fit tools

Fit, diagnose, summarize, predict, and simulate distributional models.

drmTMB(): Fit a distributional regression model with TMB
drm_control(): Control fitting and fitted-object storage
objective_at(): Evaluate the fitted objective at a supplied point
miss_control(): Configure missing-data handling
drm_phylo_penalty(): Penalty / prior specification for a phylogenetic location-scale fit
drm_phylo_penalty_sweep(): Prior-sensitivity sweep for the phylogenetic correlation penalty
native_reader_contracts: Stable native reader contracts
check_drm(): Check convergence and diagnostic flags for a drmTMB fit
convergence_status(): Convergence status for a drmTMB fit
drm_provenance(): Build provenance of the installed drmTMB package
is_converged(): Check whether a fit converged
confint(<drmTMB>): Confidence intervals for fitted model parameters
profile_targets(): List confidence-interval targets for a fitted model
profile(<drmTMB>): Compute profile-likelihood curves for fitted model targets
coevolution_cor() coevolution_vc() coevolution_summary(): Coevolution accessors for q = 4 structured bivariate location-scale fits
corpairs(): Extract fitted correlation pairs
fitted(<drmTMB>): Extract fitted response values
fixef() coef(<drmTMB>): Extract fixed-effect coefficients
heritability() icc() repeatability(): Heritability, ICC, and repeatability accessors
imputed(): Extract fitted missing-predictor summaries
vcov(<drmTMB>) logLik(<drmTMB>) AIC(<drmTMB>) BIC(<drmTMB>) nobs(<drmTMB>) df.residual(<drmTMB>) deviance(<drmTMB>): Extract standard model-fit quantities
anova(<drmTMB>): Likelihood comparison guard for drmTMB fits
aicc() anova(<drmTMB_julia>): Corrected Akaike information criterion (AICc)
chibar_pvalue() lrt_boundary(): Boundary-corrected likelihood-ratio test for variance components
marginal_parameters(): Marginal summaries of predicted distributional parameters
prediction_grid(): Build prediction grids for distributional-parameter summaries
predict_parameters(): Predict distributional parameters in long format
predict(<drmTMB>): Predict distributional parameters
ranef(): Extract conditional random-effect estimates
residuals(<drmTMB>): Extract model residuals
rho12(): Extract residual correlation rho12
sigma(<drmTMB>): Extract fitted scale or dispersion
simulate(<drmTMB>): Simulate from a fitted model
structured_effects(): Extract structured-effect metadata
summary(<drmTMB>): Summarize a fitted model
weights(<drmTMB>): Extract likelihood weights
associate_pairs(): Associate two frozen marginal drmTMB fits
association(): Extract a pair association estimate
biv_associate(): Fit two margins and construct a frozen-margin association in one call
vcov(<drm_pair_association>): Alpha-scale covariance for a frozen-margin association
confint(<drm_pair_association>): Confidence intervals for a frozen-margin association
predict(<drm_pair_association>): Predict a frozen-margin pair association

Distributional outputs and adequacy

A first-class fitted distribution for every family, plus the adequacy diagnostics and centile/exceedance outputs built on it (#747, #748).

fitted_distribution(): Fitted distribution accessor
exceedance(): Exceedance probability from a fitted model
centile_chart(): Model-conditional centile chart
worm_plot(): Worm plot of randomized quantile residuals
qq_plot(): Normal QQ plot of randomized quantile residuals

Julia engine methods

Post-fit methods for optional Julia-engine fits; availability depends on the admitted model and inference route.

confint(<drmTMB_julia>): Confidence intervals for an engine = "julia" fit
predict(<drmTMB_julia>) predict(<drmTMB_julia_xfam>): Predict from a Julia-bridge drmTMB fit
summary(<drmTMB_julia>): Summarise an engine = "julia" drmTMB fit
weights(<drmTMB_julia>): Prior weights of an engine = "julia" fit
coef(<drmTMB_julia_joint>) vcov(<drmTMB_julia_joint>) nobs(<drmTMB_julia_joint>) predict(<drmTMB_julia_joint>) imputed(<drmTMB_julia_joint>) summary(<drmTMB_julia_joint>) confint(<drmTMB_julia_joint>): Inspect a Julia joint missing-predictor fit
rho_latent(): Extract a latent-scale correlation from a cross-family Julia fit
summary(<drmTMB_julia_xfam>): Summary for a cross-family Julia fit
vcov(<drmTMB_julia_xfam>): Extractor unavailable for a legacy cross-family Julia fit

Visualization

Optional plotting helpers for post-fit tables. Exported plotting functions appear here.

plot(<profile.drmTMB>): Plot profile-likelihood curves
plot_corpairs(): Plot fitted correlation-pair summaries
plot_parameter_surface(): Plot predicted distributional-parameter surfaces