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drmTMB: Distributional Regression Models Using Template Model Builder

Fast distributional regression models for univariate and bivariate responses using Template Model Builder. The current implementation focuses on Gaussian, Student-t, and skew-normal location-scale models, known sampling covariance, phylogenetic location effects, random-effect scale models, bivariate residual correlation, positive-continuous, 'Tweedie' semi-continuous, strict-proportion, zero-one bounded, and denominator-aware proportion families, fixed-effect Bernoulli/binomial event-probability models, and fixed-effect Poisson, negative-binomial, zero-inflated, zero-truncated, hurdle count, and ordinal cumulative-logit models. Additional response-family models are staged for later phases. Every fitted family also exposes a distributional-output and adequacy layer: randomized quantile-residual worm and QQ plots that detect fixed-effect shape and atom misspecification, and conditional-quantile, exceedance, and centile outputs with plug-in (uncalibrated) intervals.

Version: 0.7.0
Depends: R (≥ 4.1.0)
Imports: cli, lifecycle, Matrix (≥ 1.6.0), methods, stats, TMB (≥ 1.9.6), utils
LinkingTo: RcppEigen, TMB
Suggests: ape, callr, detectseparation (≥ 0.4.0), emmeans, extraDistr, fmesher, glmmTMB, ggplot2, JuliaCall, knitr, lme4, MASS, metadat, metafor, mvtnorm, nlme, numDeriv, ordinal, palmerpenguins, pkgload, rmarkdown, sf, spelling, statmod, testthat (≥ 3.0.0), tweedie, withr
Published: 2026-09-15
DOI: 10.32614/CRAN.package.drmTMB (may not be active yet)
Author: Shinichi Nakagawa ORCID iD [aut, cre, cph]
Maintainer: Shinichi Nakagawa <itchyshin at gmail.com>
BugReports: https://github.com/itchyshin/drmTMB/issues
License: GPL (≥ 3)
Copyright: see file COPYRIGHTS
URL: https://itchyshin.github.io/drmTMB/, https://github.com/itchyshin/drmTMB
NeedsCompilation: yes
Language: en-GB
Citation: drmTMB citation info
Materials: README, NEWS
CRAN checks: drmTMB results

Documentation:

Reference manual: drmTMB.html , drmTMB.pdf
Vignettes: Adding distribution families (source, R code)
Animal models and additive relatedness (source, R code)
Two-tree phylogenetic interactions (source, R code)
Changing residual coupling with rho12 (source, R code)
Bivariate non-Gaussian models: choose a joint or staged association (source, R code)
Can I fit and report this model? (source, R code)
Comparing drmTMB with other packages (source, R code)
Errors, warnings, and convergence (source, R code)
Count abundance and extra zeros (source, R code)
Association between mixed outcome pairs (source, R code)
Choosing response families (source, R code)
Distributional regression with drmTMB (source, R code)
First-week intervals: fit, profile, and boundary (source, R code)
Formula grammar (source, R code)
Implementation map (source, R code)
Julia engine: future support (source, R code)
Working with large data (source, R code)
When variance carries signal, Part 2: location-scale-scale models (source, R code)
When variance carries signal, Part 1: location-scale models (source, R code)
Random-effects meta-analysis with known sampling variances (source, R code)
Handling missing data (source, R code)
What can I fit today? (source, R code)
Model selection with AIC and BIC (source, R code)
Phylogenetic mixed models (source, R code)
Proportions and success rates (source, R code)
Known-matrix relatedness with relmat (source, R code)
Robust continuous responses (source, R code)
Implemented source map (source, R code)
Coordinate-spatial structured effects (source, R code)
Structural dependence overview (source, R code)
Testing likelihoods (source, R code)
Which scale are you modelling? (source, R code)

Downloads:

Package source: drmTMB_0.7.0.tar.gz
Windows binaries: r-devel: not available, r-release: not available, r-oldrel: not available
macOS binaries: r-release (arm64): not available, r-oldrel (arm64): drmTMB_0.7.0.tgz, r-release (x86_64): drmTMB_0.7.0.tgz, r-oldrel (x86_64): drmTMB_0.7.0.tgz

Linking:

Please use the canonical form https://CRAN.R-project.org/package=drmTMB to link to this page.

These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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