{causact} 📦 v0.5.8 is on its way to CRAN. Learn computational Bayesian inference using this intuitive and visual #rstats package. Release includes a little intro vignette: cran.r-project.org/web/packages...

🧠 LLMs aren't technically Bayesian, but they're conditional probability powerhouses! They train with maximum likelihood yet output evolving token probabilities that update with each new piece of info. This visual captures how a neutral stock trend shifts up or down as new words enter the prompt.

🚀 Causality refresher! 🚀

Check out this Shiny app that uses DAGs to show how including (or controlling for) a variable (z) can help or hurt your causal inference for how x -> y. Be sure to block your back door! 🎯

{causact} 📦 v0.5.7 is on its way to CRAN. {causact} 📦 helps you visualize your Bayesian modelling assumptions using #rstats and then automates lightning fast inference using #numpyro behind the scenes. Give it a try!