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GlmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling

Bibliographic Data

ID23327360
AuthorsE Brooks Mollie (University of Zurich), Kasper Kristensen (0000-0003-3425-3762, University of Zurich), J van Benthem Koen (University of Zurich), Árni Magnússon (0000-0003-2769-6741, University of Zurich), W Berg Casper (University of Zurich), Anders Nielsen (0000-0002-3294-6234, University of Zurich), James S Hans (University of Zurich), J Skaug Hans, Martin Mächler (0000-0002-8685-9910, University of Zurich), M Bolker Benjamin (0000-0002-8374-3226, University of Zurich)
Year2017
Volume9
Issue2
Pages378
Publication date2017-01-01
Peer ReviewedYes
Open AccessYes
TypeARTICLE
VenueThe R Journal (JOURNAL)
Journal identifiersISSN: 2073-4859 • E-ISSN: 2073-4859
PublisherThe R Foundation (PUBLISHER)
DOI10.32614/rj-2017-066
OpenAlexW2786358356
LanguageEN
Citations received449
References cited7

Count data can be analyzed using generalized linear mixed models when observations are correlated in ways that require random effects. However, count data are often zero-inflated, containing more zeros than would be expected from the typical error distributions. We present a new package, glmmTMB, and compare it to other R packages that fit zero-inflated mixed models. The glmmTMB package fits many types of GLMMs and extensions, including models with continuously distributed responses, but here we focus on count responses. glmmTMB is faster than glmmADMB, MCMCglmm, and brms, and more flexible than INLA and mgcv for zero-inflated modeling. One unique feature of glmmTMB (among packages that fit zero-inflated mixed models) is its ability to estimate the Conway-Maxwell-Poisson distribution parameterized by the mean. Overall, its most appealing features for new users may be the combination of speed, flexibility, and its interface's similarity to lme4.

Flexibility (engineering) · Generalized linear mixed model · Statistics · Zero (linguistics) · Applied Mathematics · Computer Science · Genetic and phenotypic traits in livestock · Mathematics · Statistical Methods and Bayesian Inference · Statistical Methods and Inference

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Unique citing works449
Citations per year24,94
Citation span2008 - 2026 (19)
Citation velocitycurrent
Highly citedYes
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