Francisco Rodriguez-SanchezA #mcmc_stan #rstats question:
Is it possible to retrieve the seed used for a model fitted with cmdstanr?
In rstan there is get_seed, but can't find similar thing for cmdstanr
Thanks! @mcmc_stan
F. Javier Rubio"Past, Present and Future of Software for Bayesian Inference" by Štrumbelj et al. (2024). Statistical Science.
https://doi.org/10.1214/23-STS907
#rstats #Python #JuliaLanguage #mcmc_stan #INLA #MCMC #BUGS #blackjax #JAGS #HMC #Matlab #Mathematica #ABC #Turing
Past, Present and Future of Software for Bayesian Inference
Software tools for Bayesian inference have undergone rapid evolution in the past three decades, following popularisation of the first generation MCMC-sampler implementations. More recently, exponential growth in the number of users has been stimulated both by the active development of new packages by the machine learning community and popularity of specialist software for particular applications. This review aims to summarize the most popular software and provide a useful map for a reader to navigate the world of Bayesian computation. We anticipate a vigorous continued development of algorithms and corresponding software in multiple research fields, such as probabilistic programming, likelihood-free inference and Bayesian neural networks, which will further broaden the possibilities for employing the Bayesian paradigm in exciting applications.
Ed Merkleblavaan 0.5-1 is now on CRAN, including initial functionality for two-level structural equation models. Estimation happens via #mcmc_stan
If you don't know these models, they are multivariate Gaussian models with three levels (e.g., multiple response variables within people within schools).
Some further info is here:
https://ecmerkle.github.io/blavaan/articles/multilevel.html
Martin ModrákNew version of cmdstanr exposes Stan functions and allows you to directly unconstrain parameters (super useful for seeing parameters as the sampler sees them)! A huge win!
Michael FrankeGetting started here. Expect me to talk about #stats, #bayes, #brms, #mcmc_stan, #probprag, #emacs, #cogsci, #cogmod, #pragmatics and more.
Seth Axen 🪓 Things are coming together for #ArviZ's InferenceData (https://github.com/arviz-devs/InferenceObjects.jl) to be a supported output type for #Turing and #JuliaLang's 
#Stan interface, similarly to how it is for #PyMC.
For details, see https://github.com/TuringLang/MCMCChains.jl/issues/381 and https://github.com/StanJulia/StanSample.jl/issues/60
Martin Modrák - Test accountA free online conference on Bayesian analysis of spatiotemporal data with the #Stan language tomorrow.
StanConnect 2022: "Stan Through Space and Time"
Date: October 31st, 8am-12:30pm EDT
There's an incredible lineup -- check out the speakers, abstracts and register now: https://eventbrite.com/e/stanconnect-2022-stan-through-space-and-time-tickets-440757677077
Hosted by Jamie Hogg and the Stan team.