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#brms

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Dr Mircea Zloteanu 🌼🐝

#statstab #299 The role of "max_treedepth" in No-U-Turn?

Thoughts: Once you start using more complex models you will run into issues at some point; this is one; good solution guide.

#brms #bayesian #modeling #stats #issues #solutions #stan #forum

discourse.mc-stan.org/t/the-ro

The Stan Forums · The role of "max_treedepth" in No-U-Turn?Hi, I am working on a model where I saw the treedepth could reach 14, leading to a slow fitting. I wanted to know better the role of this parameter, thus I tested a simpler model with different max_treedepth values. It seems for me that too low max_treedepth would lead to inefficient sampling (low ESS). Could someone explain how max_treedepth works in the algorithm? What is the appropriate value of max_treedepth when use the stan() function in rstan package? Thank you.
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Pierre de Villemereuil

Incidentally, our companion #rstats Reacnorm package is now live in CRAN, so it's as easy as `install.packages("Reacnorm")` and `vignette("TutoReacnorm")` to access our nice tutorial on analyse reaction norms using the #brms and Reacnorm package.

cran.r-project.org/package=Rea

cran.r-project.orgReacnorm: Perform a Partition of Variance of Reaction NormsPartitions the phenotypic variance of a plastic trait, studied through its reaction norm. The variance partition distinguishes between the variance arising from the average shape of the reaction norms (V_Plas) and the (additive) genetic variance . The latter is itself separated into an environment-blind component (V_G/V_A) and the component arising from plasticity (V_GxE/V_AxE). The package also provides a way to further partition V_Plas into aspects (slope/curvature) of the shape of the average reaction norm (pi-decomposition) and partition V_Add (gamma-decomposition) and V_AxE (iota-decomposition) into the impact of genetic variation in the reaction norm parameters. Reference: de Villemereuil & Chevin (2025) <<a href="https://doi.org/10.32942%2FX2NC8B" target="_top">doi:10.32942/X2NC8B</a>>.
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Christian Röver

A very interesting workshop on "Hierarchical models in preclinical research" finished today in Göttingen. This was a joint undertaking of the IBS-DR working groups "Non-clinical statistics" and "Bayes Methods", and included an extensive Tutorial on #brms by Sebastian Weber and Lukas Widmer. Some of the material is available on the meeting website:

biometrische-gesellschaft.de/a

Workshop participants in the Göttingen State and University LIbrary.
#Bayesian#rstats#MedStatGoe
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