The struct() defines the RHS correlation matrix while the LHS formula defines (as usual) a covariance in terms of lme4-style for the REs.

I'm not sure if I am breaking/abusing the usual random-effect syntax, but it seemed sensible to me (does #glmmTMB do something similar @bbolker.bsky.social?).

New on the gllvm front: functionality for fitting univariate #GLMMs: gllvmVA(). You may wonder why this is useful, with great packages such as #lme4 and #glmmTMB at your disposal.

Around 3 years ago, we started writing papers during our weekly lab meetings. This is the first one from our new lab at
@ualberta.bsky.social

Location-Scale Models for Ecologists!

preprint: ecoevorxiv.org/repository/v...
tutorial: ayumi-495.github.io/Eco_location...

Enjoy! #glmmTMB #brms

Just added a zero-inflated binomial option to #gllvm. ZIP, ZINB, ZIBeta were already supported. At some point it would be cool to fully extend this into model-based ordination of zero-inflated components (similar to #glmmTMB and multispecies occupancy).

If I could only find the time..

Model‐based ordination for phenological studies: From controlling sampling bias to inferring temporal associations Willig et al. (Methods in Ecology and Evolution, 15, 868–885, 2024) cautioned that unequal sampling effort and pseudoreplication can bias the characterisation of species phenology using circular s...

Pretty cool; Lai (2025, besjournals.onlinelibrary.wiley.com/doi/10.1111/...) advocates for using GLLVMs in phenological studies. They demonstrate with the #glmmTMB package while referring to the #gllvm package for temporally structuring LVs, relaxing the temporal independence assumption in glmmTMB.

@bbolker.bsky.social I have a random probit model, and #glmmTMB fits much slower than #gllvm (see below with VA, LA is about half the time of glmmTMB). Any idea what's going on?

Has anyone an idea if it is appropriate (and if so, how?) to model a dispersion parameter in #glmmTMB (as alternative to robust/HC standard errors) when inverse probability weights are included in the model? For which parameter(s) should the dispersion be modeled? @bbolker.bsky.social maybe?

#Poisson regression with #mgcv and #glmmTMB in #rstats just rocks

Comparing Bayesian Approaches

#statstab #181 Comparing Bayesian Approaches by @jebyrnes

Thoughts: Compares running models in #rethinking, #stan, #brms, #inla, and #glmmTMB via #TMBstan. It's nice to have options.

#bayes #bayesian #rstan #r #stats #rstats

biol609.github.io/lab/alt_to_r...

I have just realised that {glmmTMB} has been downloaded far too rarely so far. Maybe people haven't recognized how flexible and strong this package became? Install it now, it's the {brms} in the frequentist world! cran.r-project.org/package=glmm... #rstats #glmmTMB (sorry for x-post, but it's x-mas)

Hey #mixedmodel #rstats peeps - anyone know of a package or function that does for #glmmTMB what merTools::predictInterval() does for #lme4? #wantingToMoveEverythingOver

For the record, it was a zero augmented beta regression that I fit with #glmmTMB. Hell yeah.