#statstab #477 Simulating data for Dirichlet regression with varying estimates

Thoughts: Interesting thread about an underused model.

#Dirichlet #brms #poweranalysis #rstats #proportions #stan #forum

https://discourse.mc-stan.org/t/simulating-data-for-dirichlet-regression-with-varying-estimates/35325

#statstab #466 Bayesian workflow: Prior determination, predictive checks and sensitivity analyses

Thoughts: Having a good bayesian work flow can be challenging with complex models.

#priors #bayesian #sensitivityanalysis #posterior #ppc #brms

https://pablobernabeu.github.io/2022/bayesian-workflow-prior-determination-predictive-checks-and-sensitivity-analyses/

#statstab #464 Plotting p-check interaction {brms}

Thoughts: Annoyingly #brms doesn't natively allow plotting for interactions (that I know of). The forum has a solution.

#ppc #posterior #bayesian #modelfit #diagnostic #rstats #r #stan

https://discourse.mc-stan.org/t/plotting-pp-check-interactions/31936

#stats Q: for a bayesian negative binomial (in #brms), who should I think about the prior on phi (shape)? How can I connect it to either theory or stat desiderada?

Examples, tutorials, resources appreciated

(it all seems a bit abstract to me)

Rekomendasi Trading bulan ini adalah BRMS & PSAB kembali mencuri momentum seiring harga emas.

Mulai dari info insider trading dan perspektif investor.

Apakah Sentimen komoditas menguat, peluang masih terbuka?

Tetap perhatikan volatilitas pasar di Bareksa.

#Bareksa #TradingSaham #BRMS #PSAB #HargaEmas #GoldUpdate #SahamTambang #MarketToday

https://www.bareksa.com/berita/saham/2025-11-11/rekomendasi-trading-saham-hari-ini-brms-psab-harga-emas-kembali-tembus-us4100

To the Bayesian pros: Is this is an OK-ish loo_ribbon plot?
Im using pp_check from #brms
Maybe @paul_buerkner could help 😅 ?

The ppd looks like this.
Im not super happy because that small bimodality is not well captured, but perhaps is too small and it doesnt matter?

#Bayesian #BayesInference #BRMS

#statstab #450 Fitting GAMs with brms

Thoughts: Assuming linearity of your continuous predictors is not needed when you can add wiggles!

#gam #glmm #linearmodel #modelling #brms #rstats #bayes #tutorial #splines #r

https://fromthebottomoftheheap.net/2018/04/21/fitting-gams-with-brms/

#statstab #437 Speeding up categorical models in {brms}

Thoughts: As I'm currently annoyed with how long some models take, I'm sharing resources to help others.

#brms #categorical #efficiency #rstats #modelling #r #stan

https://rpubs.com/mvuorre/faster-categorical-brms-models

#statstab #436 {chkptstanr} Checkpoint MCMC Sampling with Stan

Thoughts: This! Allows you to stop and start the sampling in {brms}. Can be a lifesaver.

#rstats #stan #brms #mcmc #efficiency #stanr #hmc #bayesian

https://donaldrwilliams.github.io/chkptstanr/

#statstab #435 Guide to understanding the intuition behind the Dirichlet distribution

Thoughts: Useful for composite proportions, but take ages in brms.

#brms #Dirichlet #proportions #modelling #rstats #r #betareg

https://www.andrewheiss.com/blog/2023/09/18/understanding-dirichlet-beta-intuition/

R: how many cores do you want to use?
Me: Yes.

#R #brms #bayesian #rstats

#statstab #401 Common issues, conundrums, and other things that might come up when implementing mixed models

Thoughts: GLMMs are cool, but come with their own quirks.

#glmm #lmer #brms #mixedeffects #hierarchicalmodels #r

https://m-clark.github.io/mixed-models-with-R/issues.html

#statstab #398 Eta^2 for bayesian models {effectsize}

Thoughts: Great resource, but scroll to "Eta Squared from Posterior Predictive Distribution"

#effectsize #eta2 #bayesian #brms #r

https://easystats.github.io/effectsize/reference/eta_squared.html#eta-squared-from-posterior-predictive-distribution

New on the blog: Using Bayesian tools to be a better frequentist

Turns out that for negative binomial regression with small samples, standard frequentist tools fail to achieve their stated goals. Bayesian computation ends up providing better frequentist guarantees. Not sure this is a general phenomenon, just a specific example.

https://www.martinmodrak.cz/2025/07/09/using-bayesian-tools-to-be-a-better-frequentist/

#rstats #Bayesian #brms #stan

okay #rstats #rstan #stan hivemind:

do you have any examples of Stan models (incl #brms) running in production, especially attached to Shiny apps where responsiveness/compute time is pretty important (and interfacing with non-quant people)?

What tricks do you use?

Please send blogs, packages, repos, anecdotes! :)

Please do not send: suggestions that I use an empirical Bayes/frequentist framework. I know how to do that :)

I now understand better why wiener waffeln exist.... every time my initial values are rejected I eat one
#rstats #brms #rstan #ddm

#statstab #350 Communicating causal effect heterogeneity
By @matti

Thoughts: Cool guide on properly communicating uncertainty in effects.

#bayesian #uncertainty #ggplot #r #brms #tidybayes #heterogeneity

https://vuorre.com/heterogeneity-uncertainty/

#statstab #328 How to Assess Task Reliability using Bayesian Mixed Models
by @Dom_Makowski

Thoughts: Nice walkthrough using {brms}, with code, data gen, and plots.

#r #bayesian #mixedeffects #reliability #brms

https://realitybending.github.io/post/2024-03-18-signaltonoisemixed/

#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

https://discourse.mc-stan.org/t/the-role-of-max-treedepth-in-no-u-turn/24155

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.

https://cran.r-project.org/package=Reacnorm