Aki Vehtari

StanCon 2026 Oral presentation deadline (25th of February) Hi all, Just a quick reminder for StanCon 2026 (Uppsala, 17–21 August): if you’re planning to give an oral presentation, the submission deadline is 25 February (AoE). If you have a talk in mind, plea...

🔥🔥 StanCon 2026 Oral Presentation Submission Deadline on the 25th of February 🔥🔥

discourse.mc-stan.org/t/stancon-20...

I started making this R package 6 years ago. I finally have it in a state I'm happy with, thanks to Claude Code #Rstats github.com/MattCowgill/...

Announcing the third keynote speaker for StanCon 2026 We’re happy to share the third keynote speaker for StanCon 2026! StanCon 2026 will take place 17–21 August 2026 in Uppsala, Sweden. Kaitlyn Johnson, London School of Hygiene and Tropical Medicine Jo...

🔥 StanCon 2026 third keynote announced 🔥
Kaitlyn Johnson,
London School of Hygiene & Tropical Medicine
More information here
discourse.mc-stan.org/t/announcing...
@mc-stan.org

Slowly populating the ISEC website with accepted workshop info, if anyone wants to take a peek 👀 statisticalecology.org

Official announcements & full info coming next week.

I think composable models are the future, and it would be great to have more tools for building composable models. This is a nice talk about the benefits

YouTube video by Juniper Consortium Seminars Sam Abbott (LSHTM): Composable probabilistic models can lower barriers to rigorous ID modelling

I had a great time talking at the Juniper seminar series last week about composable infectious disease models. Some very good discussion after the talk. The recording is now up!

youtu.be/FQYOqGnbJWA?...

1/2 Nail in the coffin of dichotomania: @erik-van-zwet.bsky.social 's paper with @stephensenn.bsky.social and myself just published: onlinelibrary.wiley.com/doi/10.1002/... with extended discussion at discourse.datamethods.org/t/dichotomiz... #Statistics #StatsSky #rct #clinicaltrial

StanCon 2026 Deadline for oral presentations in ten days (25th of February) Hi everyone, The submission deadline for contributing for oral presentations is one week from now, on the 25th of February. Submit your abstract here: Abstracts – Stan Conference 2026 — The Local Or...

StanCon 2026 deadline for oral presentations 25th of February! discourse.mc-stan.org/t/stancon-20...

If you have any questions, ask in Stan discourse or contact one of the local organizing committee members

The streets were already too well cleared and sprinkled with gravel yesterday after lunch, so that I had to walk back home, but today the views are even prettier with sunshine

Photo of snowy scenery

Finally enough snow that I could ski from home to campus

When are Bayesian model probabilities overconfident? Bayesian model comparison is often based on the posterior distribution over the set of compared models. This distribution is often observed to concentrate on a single model even when other measures of...

See also arxiv.org/abs/2003.04026

In this same journal, Arnold Zellner published a seminal paper on Bayes' theorem as an optimal information processing rule. This result led to the variational formulation of Bayes' theorem, which is the central idea in generalized variational inference. Almost 40 years later, we revisit these ideas, but from the perspective of information deletion. We investigate rules which update a posterior distribution into an antedata distribution when a portion of data is removed. In such context, a rule which does not destroy or create information is called the optimal information deletion rule and we prove that it coincides with the traditional use of Bayes' theorem.

arXiv📈🤖
Optimal information deletion and Bayes' theorem
By Montcho, Rue

I reported this, and they have now fixed it. They told they had tested the survey form with several people before publishing it, but I guess no-one else was trying to find the middle of the scale

Response scale with options 0 - Not at all likely, 1, 2, 4, 5, 6, 7, 8, 9, 10 Extremely likely

I felt confused, and it took me a few seconds to realize why

Etsimme tietotekniikan lehtoreita Aalto-yliopistoon kokoaikaisiin, toistaiseksi voimassa oleviin tehtäviin! 🌟
Alueet:
✅ Bioinformatiikka, biostatistiikka ja terveysdatatiede
✅ Tietotekniikka: ohjelmointi, algoritmit ja teoria
✅ Ohjelmistotuotanto
📍Hae 16.3.2026 mennessä. Lisätiedot ja ohjeet 👇

Posterior-SBC now also with peer-review stamp in Statistics and Computing doi.org/10.1007/s112... (update your bib files)

Compositional data (proportions that sum to 1) behave in ways standard models aren’t built for

I walk through why Dirichlet regression is often the right tool & what extra insight it gives using a real ex of eyetracking

#Dirichlet #r #brms #guide #eyetracking

open.substack.com/pub/mzlotean...

Palkkaamme suomea osaavia lehtoreita: www.aalto.fi/fi/avoimet-t...

The building blocks exist, but for a ready made example on how to do it, it's best to ask the authors of that paper

Efficient Uncertainty Propagation in Bayesian Two-Step Procedures Bayesian inference provides a principled framework for probabilistic reasoning. If inference is performed in two steps, uncertainty propagation plays a crucial role in accounting for all sources of un...

The second part computation can be made faster using importance sampling arxiv.org/abs/2505.10510

This is known as cut posterior. Stan developers have discussed possibility of adding support for cut in Stan, but it hasn't been prioritised as it can often be achieved just running inference for first part, and then run parallely the second part with many datasets (as in multiple imputation)

Species distribution modeling with expert elicitation and Bayesian calibration Species distribution models (SDM) are key tools in ecology, conservation, and natural resources management. They are traditionally trained with data on direct species observations. However, if collec....

Ever wondered how to use supra-Bayesian approach in species distribution modeling (SMDs). Well we present a framework for it and exemplify it with real data on fish reproduction area estimation.

nsojournals.onlinelibrary.wiley.com/doi/10.1002/...
1/3

In CmdStanR, you just pass the pathfinder object to sample init argument, no need to convert

GitHub - VisruthSK/stanflow: R Package for a Mildly Opinionated Stan Bayesian Workflow R Package for a Mildly Opinionated Stan Bayesian Workflow - VisruthSK/stanflow

First release of stanflow! v0.1.0 was a few days later than I'd like, but its up now.

Stanflow is a metapackage a la tidyverse for a Stan Bayesian workflow--see the README for more details/features!

Feedback/issues/PRs are always appreciated.

#rstats #bayes

Divergent transitions in Hilbert Space Gaussian process posteriors and how to avoid them | Nikolas Siccha | Generable How to train your favorite basis function based approximation to Gaussian Processes.

Nikolas Siccha's blog post "Divergent transitions in Hilbert Space Gaussian process posteriors and how to avoid them" shows some cool results he started working on when at Aalto www.generable.com/post/hsgp-re...

With more than 14k lines of code!

Bayesian Workflow Bayesian statistics and statistical practice have evolved over the years, driven by advancements in theory, methods, and computational tools. This book explores the intricate workflows of applied Baye...

The publisher estimates the Bayesian Workflow book will ship in June www.routledge.com/Bayesian-Wor...

I'm watching this year's lectures to see how @rmcelreath.bsky.social, one of the soon to be published Bayesian Workflow book co-author, teaches workflow. So far looking good!

StanCon 20206 International Conferene on Bayesian Inference and Probabilistic Programming 17-21 August, 2026 Uppsala, Sweden

Three weeks time to submit contributed talk abstract to StanCon 2026! You can also submit a poster abstract early, if you need to make early travel plans. There will be travel and accommodation support for students, too!

More information about submitting at www.stancon2026.org/abstracts/

Watching @rmcelreath.bsky.social's both A and B lectures feels like a watching a movie which jumps between two different time periods