🔥 We’re pleased to announce two confirmed tutorials for #StanCon2026 🔥
_An introduction to applied Bayesian statistics with Stan_ — Mitzi Morris
_Bayesian model diagnostics: Workflows and software tools_ — Osvaldo Martin, Teemu Säilynoja, and Noa Kallioinen
More info: stancon2026.org/tutorials/
The great @eddelbuettel.com invited me to his STAT447 class at the University of Illinois.
If you'd like to hear me speak about the interpretation of statistical models in #RStats, using the {marginaleffects} 📦, check out the video!
www.youtube.com/watch?v=v3TX...
occARU: Bayesian (multispecies) occupancy models for ARU data using @mc-stan.org. Automated recording units (ARUs) like camera traps produce rich time series which warrant going beyond occupancy and focusing on detection rates. 1/n
mhollanders.github.io/occARU/
Finally finished up a blog post on estimating Bradley–Terry models using brms.
www.m-flynn.com/posts/2025-1...
Some new work on (dynamic path length) Riemannian manifold HMC. RMHMC with a block-diagonal mass matrix admits an explicit (symmetric & reversible) integrator. We find the parameters of the sampler, including the hierarchical mass matrix using on-line adaptation.
For reasons that are certainly unrelated to grant applications, does anyone know of (ideally with some evidence) uses of tools I have contributed to (scoringutils, epinow2, epinowcast, epidist, primarycensored, episoon, epinow, censoreddistributions ...) from different parts of the world?
Very excited to announce that the #BayesianWorkflow book by @statmodeling.bsky.social, @avehtari.bsky.social, @rmcelreath.bsky.social et al publishes in June! routledge.com/9780367490140 #RStats #DataScience #Bayesian
Lauren continues to write fabulous papers a lot this. This was the other week arxiv.org/abs/2603.29134
ArviZ now has built-in tools for prior & likelihood sensitivity analysis via power-scaling!
Instead of fitting multiple models with different priors, you fit once and use importance sampling to approximate the effect of perturbing the prior or likelihood.
ArviZ 1.0 brings a lot of new plotting functionality.
Check our gallery for a glimpse of what's new: python.arviz.org/projects/plo...
Amortized Bayesian Workflow
Chengkun LI, Aki Vehtari, Paul-Christian Bürkner et al.
Action editor: Tom Rainforth
https://openreview.net/forum?id=osV7adJlKD
#mcmc #generative #amortized
More details about the Bayesian Workflow book and case studies now available on the book web site avehtari.github.io/Bayesian-Wor... (but you still need to wait a bit for the book)
More details about the Bayesian Workflow book and case studies now available on the book web site avehtari.github.io/Bayesian-Wor... (but you still need to wait a bit for the book)
cover of the book "Bayesian Workflow" by Gelman, Vehtari, et al. Coming out later this year, in the summer probably.
I would have preferred to have the "draw the rest of the owl" meme on the cover, but this will do. Seems like it is on schedule, and we'll leave some typos so you know we didn't write it with AI.
Screenshot of electric car charging app showing charged -312945,53kWh -109530,86€
I was charging a rental car and I guess I should have stopped charging at this point for a big win? (Ladattu = Charged, Lopeta lataus = Stop charging)
New pre-print! I cover a range of open capture-recapture models (single survey/robust design, multistate/multievent, in (Cormack-)Jolly-Seber variants) in Stan, and provide efficient log likelihood functions. I also introduce a method to account for unequal survey intervals in the entry process.
If you care about the accuracy of the models, you should care about the accuracy of the language used when talking about the models.
I blogged and will keep adding more to this blog post series
I'm looking for a post-doc to help organize Bayesian Data Analysis course avehtari.github.io/BDA_course_A... (200 students) and to do research on Bayesian workflow users.aalto.fi/~ave/publica... at Aalto www.aalto.fi/en, Finland. Background in Bayes needed. Up to five year contract possible.
Looking for a postdoc to teach and develop Bayesian methods
statmodeling.stat.columbia.edu/2026/03/31/l...
Salary and occupational benefits are better than in academia in many other countries, and living costs are moderate (not the cheapest country but also less expensive than big cities in many countries). Finland is the world happiest country 9th time in a row
I'm looking for a post-doc to help organize Bayesian Data Analysis course avehtari.github.io/BDA_course_A... (200 students) and to do research on Bayesian workflow users.aalto.fi/~ave/publica... at Aalto www.aalto.fi/en, Finland. Background in Bayes needed. Up to five year contract possible.
Markov chain Monte Carlo (MCMC) methods remain the mainstay of Bayesian estimation of structural equation models (SEM); however they often incur a high computational cost. We present a bespoke approximate Bayesian approach to SEM, drawing on ideas from the integrated nested Laplace approximation (INLA; Rue et al., 2009, J. R. Stat. Soc. Series B Stat. Methodol.) framework. We implement a simplified Laplace approximation that efficiently profiles the posterior density in each parameter direction while correcting for asymmetry, allowing for parametric skew-normal estimation of the marginals. Furthermore, we apply a variational Bayes correction to shift the marginal locations, thereby better capturing the posterior mass. Essential quantities, including factor scores and model-fit indices, are obtained via an adjusted Gaussian copula sampling scheme. For normal-theory SEM, this approach offers a highly accurate alternative to sampling-based inference, achieving near-'maximum likelihood' speeds while retaining the precision of full Bayesian inference.
arXiv📈🤖
Approximate Bayesian Inference for Structural Equation Models using Integrated Nested Laplace Approximations
By Jamil, Rue
🎉 ggauto is now on CRAN 🎉
An #RStats package that selects better chart types, and provides more accessible styling for #ggplot2 plots 📊
Blog post explaining why I made it and how it works: nrennie.rbind.io/blog/introdu...
#DataViz
Celebrating the draft FDA Bayesian guidance document with our perspective in @jama.com. Honored to co-author w/Jack Lee (MD Anderson), Lisa LaVange (past director of Office of Biostatistics FDA CDER&president of ASA),& my Bayesian inspiration Sir David Spiegelhalter jamanetwork.com/journals/jam...
Sara Hamis, John Forslund, Cici Chen Gu, Jodie A. Cochrane: A practical introduction to ODE modelling in Stan for biological systems https://arxiv.org/abs/2603.20343 https://arxiv.org/pdf/2603.20343 https://arxiv.org/html/2603.20343
We are happy to announce the second StanCon 2026 workshop:
🔥 Bayesian Inference for Sparsity-Promoting and Edge-Preserving Priors 🔥
More information on the workshop can be found here:
www.janglaubitz.com/stancon2026
More info on Stancon 2026 in Uppsala can be found here:
www.stancon2026.org
Statistical Rethinking 2026 is done: 20 new lectures emphasizing logical and critical statistical workflow, from basics of probability theory to causal inference to reliable computation to sensitivity. It's all free, made just for you. Lecture list and links: github.com/rmcelreath/s...
