CRAN RStan and StanHeaders have been updated to version Stan 2.26. Importantly 2.26 supports both the old and the new array syntaxes. After all 200+ CRAN packages that have been built on top of RStan or StanHeaders have updated their Stan codes to use the new syntax, RStan and StanHeaders can move to Stan 2.33 which supports only the new syntax.

https://cran.r-project.org/package=rstan

#rstats #Bayesian #MCMC #Stan

Probabilistic programing is super cool. If you have ideas on how to make it cooler, think about applying to this open call from the Turing institute

https://www.turing.ac.uk/work-turing/probabilistic-programming-open-call

#stats #ml #bayesian #turing #science

🧑‍🏫Our members will be at the British Society for #Population Studies (BSPS) #conference from Monday - Wednesday next week at Keele University.

To see how we are getting involved - including a stand with our Connecting #Generations partners LCDS - head to our website to see full listings 👇👇 #bsps2023

▶️ http://www.cpc.ac.uk/news/latest_news/?action=story&id=774

#demography #migration #fertility #family #mortality #covid19 #housing #care #bayesian #ethnicity

do the #statistics or #ML folks have any suggestions about packages (ideally in python) to train #Bayesian Gaussian mixture models? I was using the sklearn package but suspect there is something better

yessssss this brms bayesian model for a conjoint survey experiment took 3 hours to fit, estimated nearly 40,000 unique parameters, takes up 4 GB of space, and is most definitely way overkill, but IT CONVERGED AND WORKS GLORIOUSLY #rstats #bayesian #statsodon

🚀 Just wrapped up an insightful session at PyMCon Web Series! 💡

Missed it? No worries! Here's the recording of Bill Engels' talk on "Introduction to Hilbert Space GPs (HSGPs) in PyMC" 👉 https://www.youtube.com/watch?v=ri5sJAdcYHk

🌟 In this talk, Bill introduced a PyMC Hilbert Space Gaussian Process (HSGP) implementation and showed via case studies how it fills a few key gaps in the PyMC GP library: fast GPs as model subcomponents, and fast GPs with non-Gaussian likelihoods 📊💡.

#PyMCon #bayesian #PyMC #python

CmdStan 2.33.0!

This new release brings two new exciting features:
- a new Stan language type - tuples
- a new VI algorithm - Pathfinder.

The release also features some new functions - mostly related to tuples, and other minor improvements.

There are also a number of long-deprecated language features that have now become errors with this version.

For details, see the blog post: https://blog.mc-stan.org/2023/09/05/release-of-cmdstan-2-33/

#Bayesian #mcmc #pathfinder #CmdStan

📢 The PyMC community team will be holding office hours to provide an outlet for the community to ask questions, get help, discuss, etc. Office hours are open to everyone, and anyone should feel welcome to attend.

📅 Date: Thursday, Sept 14, 2023
⏰ Time: 17 UTC / 10 am PT / 1 pm ET
👉 Register (for Zoom link): www.meetup.com/pymc-online-meetup/events/295908813

Office hours will last about an hour, so don't worry if you can't make it at exactly this time! see you there

#pymc #bayesian #statistics

**Fully funded postdoc and doctoral student positions in various topics including Bayesian modeling, probabilistic programming and workflows** with me and other professors in Aalto University and University of Helsinki, funded by Finnish Center for Artificial Intelligence @FCAI

See more topics, how to apply, and job details like salary at https://fcai.fi/we-are-hiring

#Bayes #Bayesian #ML #AI #Job #PostDoc #PhD

Ecological times series analysis using STAN and R packages mvgam and berms #bayesian #timeseries #ecology

https://github.com/nicholasjclark/physalia-forecasting-course

(1/2) Julia Bootcamp 🚀🚀🚀

While googling about Bayesian statistics, I found this awesome resource - Julia for Economists Bootcamp by Cameron Pfiffer. The course was recorded as part of Julia's sessions at Stanford's GSB. The course covers the following topics:
✅ Julia basics
✅ Parallelization
✅ Optimization and Automatic Differentiation
✅ High-performance Julia
✅ Computational Bayesian statistics

#julialang #bayesian #statistics #datascience

Hi, I'm using #JAGS (just another Gibbs sampler) and I need to setup a conditional with four conditions.
I don't think JAGS has a powerful ifelse statement to control flow (but I may be wrong). Some people pointed me to the step function but I don't get it 😰

Any idea to write a conditional structure for 4 conditions?? It should be trivial to do!
#bayes #bayesian #statistics

'Variational Inverting Network for Statistical Inverse Problems of Partial Differential Equations', by Junxiong Jia, Yanni Wu, Peijun Li, Deyu Meng.

http://jmlr.org/papers/v24/22-0006.html

#generative #bayesian #variational

ICYMI! "Constructing State and National Estimates of Vaccination Rates from Immunization Information Systems" by Raghunathan, Kirtland, Li, White, Murthy, Lin, Harris, Gibbs-Scharf & Zell

"This article uses a #Bayesian hierarchical prediction model framework that combines information from these multiple sources. The proposed approach obtains estimates in a timely manner and, in many respects, is comparable to estimates from the national surveys."
#research
https://doi.org/10.1093/jssam/smac042

I don't think I shared this: I wrote a short paper for the last ICCM/Mathpsych (https://mathpsych.org/presentation/998#/document).

It's a computational model of self-paced reading (written in @mcmc_stan) in a framework of continuous flow of information.

@cognition @linguistics @psycholinguistics @cogsci #psycholinguistics #bayesian #stan #rstats #cogsci #psycholinguistics #ComputationalModeling

Jozsef Arato has translated Chapters 1- 5 of (my + @ShravanVasishth + Daniel Schad) Intro to Bayes for Cog Sci (https://vasishth.github.io/bayescogsci/)

You can find it here:
https://github.com/jozsarato/bayescogdat

#cogsci #Bayesian #pymc #python #bayes @cognition @cogsci

Wrt #Bayesian calculations, I don't think most brains can do that, but may try to approximate with #AnticipatoryAffect. This paper explains why:
https://www.sciencedirect.com/science/article/pii/S0896627305006574

Introduction time! Hello fediscience members! I'm a new member in this instance, but I'm not new in the fediverse. I migrated from fosstodon.org to this instance. There's nothing wrong, I just needed a place where I can post in English and Spanish. I'm an Assistant Professor at CSU Stan. I usually post about #Rstats, #Quarto , #Linux, #juliaLang, #python, #psychology, #bayesian, #aging, #dementia, #mentalHealth, and other topics that I find interesting in #science.

Targeted Active Learning for Bayesian Decision-Making

https://openreview.net/forum?id=VldyVuH0eX

#supervised #bayesian #active

Was going through old repositories; found this nice document on estimating treatment effect of a medicine for a single patient with seizures #rstats :rstats:

It goes from simple to complex:
- #Visualization & summary statistics
- Poisson regression (glm) with a treatment dummy
- Penalized poisson regression to deal with 0s
- Correcting for autocorrelation
- #Bayesian Poisson model with #stan #rstanarm
- Correcting for autocorrelation and #BayesFactors #bridgesampling

https://github.com/vankesteren/single_subject