Additional resources

Bolker's GLMM course notes https://bbolker.github.io/goettingen_2019/
Bolker's FAQ page https://bbolker.github.io/mixedmodels-misc/glmmFAQ.html
See "Where to ask questions" on the site https://glmmtmb.github.io/glmmTMB/

Books we refer to

Dunn, P. K., & Smyth, G. K. (2018). Generalized linear models with examples in R (Vol. 53). New York: Springer.
Fox, G. A., Negrete-Yankelevich, S., & Sosa, V. J. (Eds.). (2015). Ecological statistics: contemporary theory and application. Oxford University Press, USA.
Warton, D.I. (2022) Eco-stats: data analysis in ecology. From t-tests to multivariate abundances. Springer.

ADMB citation:

Fournier, D.A., Skaug, H.J., Ancheta, J., Ianelli, J., Magnusson, A., Maunder, M.N., Nielsen, A., and Sibert, J. 2012. AD Model Builder: using automatic differentiation for statistical inference of highly parameterized complex nonlinear models. Optim. Methods Softw. 27:233-249.

TMB citation:

Kasper Kristensen, Anders Nielsen, Casper W. Berg, Hans Skaug, Bradley M. Bell (2016). TMB: Automatic Differentiation and Laplace Approximation. Journal of Statistical Software, 70(5), 1-21. doi:10.18637/jss.v070.i05

glmmADMB citation:

Skaug H, Fournier D, Bolker B, Magnusson A, Nielsen A (2016-01-19). _Generalized Linear Mixed Models using 'AD Model Builder'_. R package version 0.8.3.3.

glmmTMB citation:

Mollie E. Brooks, Kasper Kristensen, Koen J. van Benthem, Arni Magnusson, Casper W. Berg, Anders Nielsen, Hans J. Skaug, Martin Maechler and Benjamin M. Bolker (2017). glmmTMB Balances Speed and Flexibility Among Packages for Zero-inflated Generalized Linear Mixed Modeling. The R Journal, 9(2), 378-400. doi: 10.32614/RJ-2017-066.