juanitorduz

I feel you, man, I really do.

This goes to this week’s reading list 💪

I could not agree more 🤜🤛!

The ArviZ core devs have done tremendous work on an improved API with a lot of novel improvements. They have put together a great migration guide: python.arviz.org/en/stable/us...

If you are an ArviZ user please take a look at it and provide feedback. Open source is all about the community 🫶

Los Amigos Invisibles #Berlin

I would be very interested to read about it!

I’ll be giving a talk ok variational inference (VI) at PyData Berlin 2025 🙂! I’ll focus on some learnings of using VI for forecasting models at scale. If you are around come and say hi.
#PyDataBerlin

Thanks for sharing! The blog post and the thread will keep me busy these days 😅

Cool trick!

Wow! That described my last week 🫠

I used to experience this and it is fucking horrible 🫠

a cartoon character is holding a bunch of money and the words shut up and take are above him ALT: a cartoon character is holding a bunch of money and the words shut up and take are above him

Wait, will you be part of that book?

Thank you 🙏

👀

I am also thinking about this problem (I’m a Bayesian, don’t hit me). I have found the early stopping simulation study in nyu-cdsc.github.io/learningr/as... very enlightening (Chapter 13.3).

A beautiful read! @markhoppus.bsky.social
#blink182

Wait, which book 🤩?

Same!

Probabilistic Time Series Analysis: Opportunities and Applications - PyMC Labs

Forecasting isn’t just about prediction — it’s about decision-making under uncertainty.

@juanitorduz.bsky.social shows how Bayesian models help:
🔹 Sparse data? Use hierarchies
🔹 Stockouts? Use censored likelihoods
🔹 Messy demand? Use priors + state spaces

Practical guide 👉 dub.sh/prob-forecas...

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Which I'll never going to use because... You know... Is Meta

Here is a first intro notebook on Bayesian Power Analysis following the method described in the paper "The Bayesian New Statistics: Hypothesis testing, estimation,
meta-analysis, and power analysis from a Bayesian
perspective" (link.springer.com/content/pdf/...)
juanitorduz.github.io/power_sample...

Here it is juanitorduz.github.io/power_sample...

Probabilistic Time Series Analysis: Opportunities and Applications - PyMC Labs

Here is a new blog post with PyMC Labs: "Probabilistic Time Series Analysis: Opportunities and Applications." We provide a collection of business cases where probabilistic methods excel in real-world applications of probabilistic time series methods.

www.pymc-labs.com/blog-posts/p...

Im very interested in the Bayesian pre-analysis precision studies. I’ll write some simulations :)

Not super related, but I enjoyed reading this last week so I can not resist sharing ;)

link.springer.com/content/pdf/...

Cohort Revenue & Retention Analysis: A Bayesian Approach We present a Bayesian approach to model cohort-level retention rates and revenue over time. We use Bayesian additive regression trees (BART) to model the retention component which we couple with a lin...

I decided to wrap these cohort modeling techniques in a little pre-print 🤗

arxiv.org/abs/2504.16216

YouTube video by PyData Allen Downey - Time Series Analysis with StatsModels | PyData Global 2024

Time Series Analysis with StatsModels

Video from my PyData Global tutorial is up now:
www.youtube.com/watch?v=foMb...

Wow! Looking forward!

juanitorduz.github.io/hsgp_intro/ 🤗