at my job I’m expectedutilitymaxxing. I chatted with @alex-andorra.bsky.social on how to make it scalable and fast in an industrial context on top of the probabilistic programming language you already love, PyMC.

OK, I reread that classic paper by Paul Meehl, and . . . statmodeling.stat.columbia.edu/2026/01/28/o...

put this guy on subway takes

In particular the latter step is often rich with modeling opportunities even if the theory of the latent phenomena is lacking. I often meet people who claim there is not enough domain expertise for a bespoke model but then go on for ten minutes about the intricacies of their measurement process.

Some people are out here practicing the One and True Scientific Method (bayes on structural economic models) and they are kind of enough to write books about how to do it.

It’s become fashionable in some circles to reject decision theory (and other basic statistical ideas) for vaguely political reasons. There are valid critiques—but also some worth being wary of. Some thoughts: statmodeling.stat.columbia.edu/2025/10/17/s...

Are you a phd student? Are you in the vicinity of one and want to help them with their bad life choices? Then this is for you! #philsci

It’s an amazing package. The website also has a bunch of neat strategies to diagnose hmc samplers, ones I haven’t seen discussed elsewhere.

“We didn’t ever hide that that’s what it was. People were mad because we were calling them effects,” she says. “Then they say to us, but they’re just associations with 20 covariates. But the point is we said that from the beginning. They’re associations with 20 covariates.”

Friend telling me about how few statisticians are actually Bayesians. It's a real shame how far we have fallen from God's light.

Mitzi Morris's new case study mc-stan.org/learn-stan/c... illustrates with hierarchical and spatial models the better efficiency of the new sum_to_zero_vector constrained parameter introduced in Stan 2.36 (2024-12). Mitzi used CmdStanPy, but the Stan code is the same with all interfaces

A brief history of tech disruptions: 2010: We are going to disrupt that horrible corporation, Blockbuster 2012: We are going to disrupt those awful cab monopolies 2014: We are going to disrupt the record labels 2022: We are going to disrupt reading and writing

Feels extremely true, watching how business leadership reacts to the long search process involved in finding a good model. The bayesian workflow literature largely assumes academic contexts where research papers are expected to be in development for a year or more.

🎄✨ 𝐌𝐞𝐫𝐫𝐲 𝐂𝐡𝐫𝐢𝐬𝐭𝐦𝐚𝐬 𝐚𝐧𝐝 𝐇𝐚𝐩𝐩𝐲 𝐇𝐨𝐥𝐢𝐝𝐚𝐲𝐬 𝐟𝐫𝐨𝐦 𝐏𝐲𝐌𝐂 𝐋𝐚𝐛𝐬! 🎁 This holiday season, we want to thank everyone in our community for your support and enthusiasm. We’re grateful to see so many of you using PyMC-Marketing and CausalPy #MerryChristmas #HappyNewYear #PyMCMarketing #CausalPy #Gratitude

This piece deftly puts words to my frustration with the way we talk about AI. It’s about education but it feels apt in business, software, etc mail.cyberneticforests.com/how-does-ope...

briefly looking up empirical papers, giving up and resorting to nature documentaries is just ... extremely philosophy.

Evolution of Similarity-Biased Social Learning (by me + Alejandro Pérez Velilla). Now in press at Evolutionary Human Sciences. Formalizes the long-standing idea that, for better or worse, it may be adaptive to ignore or down-weight information from outgroup sources. osf.io/preprints/so...

It seems Ludwig Boltzmann had a bit of a drinking problem.

New Deep Dive on Splines and Hierarchical Splines for modelling Insurance Loss curves with Bambi/PyMC. The focus is on the contrast between interpolation, extrapolation and how including extra hierarchical structure aids generalisation. nathanielf.github.io/posts/post-w...

This is an excellent (very short!) discussion of how to decide which methods to use. (How can there be so many snappy and highly relevant pieces by Gelman et al. that I haven’t read?!)

I picked up the dialectical biologist at a used bookstore a couple weeks ago. It slaps. Includes a whole chapter about pranks they played on EO Wilson along with this strategy for riches and professional success.

I've been teaching a version of this class for a couple years. The hard tradeoff is how much of the class should be spent on practical skills vs explaining why common practice in journals is bananas. Students like the class more when there are more dunks obviously!

With blackjax, nutpie, numpyro, it compiles for 60 seconds. Then the progress bar goes from 0 to 100% in the blink of an eye. I'm telling you, people enjoy horse races more than formula 1 for a reason.

I'm starting to worry that the advanced compiler-NUTS samplers that have come out in the last couple years have taken the thrill out of bayes. In pymc3, I'd stare at the progress bar with glean and horror. Sometimes, it would get abruptly faster for no reason. Sometimes, it would stop.

Dropping by a Bayesian ecology conference today to see what they are doing. Apparently, it is strapping an accelerometer onto wild sharks. Then fitting hidden markov models to classify the sharks into "resting", "methodical exploration", and "rapid exploration".

Curious about how probability distributions transform?  Ever wondered from where the term “marginal probability” comes?  Confused by those “Jacobian” things?  Have I got some writing for you.

Nancy Cartwright is so impressive. She has a MasterClass now. Even more impressive its on a subject not in her AOS.

When preferences change: www.enlightenmenteconomics.com/blog/index.p...

when u open the assignment to see those overleaf-leave-space-for-the-reader-to-draw-graphs-sized margins and the default-I-know-my-IQ-score-type font, u can just assign them an A and move onto the next one.

A great-looking book on diff kinds of modelling of social behaviour. The mammoth task of translating these models into empirically solid causal claims receives frustratingly less attention than the process of building these models. Methodology of modelling is there, methodology of translation isn’t.

I got asked to make a list of five books I like that are connected thematically with my own book. I like talking about books, so I did. Here's "The best books about (human) behavior that reward working through the math." shepherd.com/best-books/b...

The most humiliating part of replying to emails is knowing that, no matter your efforts, it’s a temporary solution to a permanent problem.

Great stuff. I make a similar point on my game theory syllabus:

Hi everyone, I wanted to introduce myself. I study methods in the mathematical social sciences. So some philosophy of science. But also a lot of model building too. My main project is articulating why generative modeling + Bayes is the Way and the Light. Here's my favorite piece of writing: