Journal article
glmmTMB balances speed and flexibility among packages for Zero-inflated Generalized Linear Mixed Modeling
National Institute of Aquatic Resources, Technical University of Denmark1
Section for Ecosystem based Marine Management, National Institute of Aquatic Resources, Technical University of Denmark2
Section for Marine Living Resources, National Institute of Aquatic Resources, Technical University of Denmark3
University of Zurich4
International Council for the Exploration of the Sea5
University of Bergen6
Swiss Federal Institute of Technology Zurich7
McMaster University8
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.
| Language: | English |
|---|---|
| Year: | 2017 |
| Pages: | 378-400 |
| ISSN: | 20734859 |
| Types: | Journal article |
| DOI: | 10.32614/RJ-2017-066 |
| ORCIDs: | Brooks, Mollie Elizabeth , Kristensen, Kasper , Berg, Casper Willestofte and Nielsen, Anders |
