Stan Map-Reduce Stan allows you to split your data into shards, calculate the log likelihoods for each of those shards, and then combine the results by summing and incrementing the target log density.
Stan’s map function takes an array of parameters thetas, real data x_rs, and integer data x_is. These arrays must have the same size.
Example This is a re-implementation of Richard McElreath’s multithreadign and map-reduce with cmdstan using Rstan instead of cmdstan.

Inspired by this thread I decided to document how you can use Stan on a AWS instance with remoter.
Creating an AMI The simplest way of doing this is to start with an Ubuntu VM and install a docker container with Remoter and Rstan. I wrote a simple bash script that does that. Just ssh into Ubuntu and run:
wget -O - https://link.ignacio.website/remoter | bash Now ssh back into the instance and modify the password in my docker-compose.

This is my list of resources for people that want to go Bayesian. This list is very incompleate and I plan to update it over the next couple of weeks.
Online videos and coursse What are Bayesian Methods? - OPRE in 60 Seconds Tiny Data, Approximate Bayesian Computation and the Socks of Karl Broman: Less than 20 minutes, and very easy to follow. Bayesian Regression Modeling with rstanarm: Very short and simple Ben Goodrich’s Bayesian Statistics for the Social Sciences: Semester long, totally worth it Videos Class material Richard McElreath’s Statistical Rethinking: Semester long, totally worth it Videos Class material Book Papers, books, vignettes, and blogs Bayesian data analysis for newcomers Speaking on Data’s Behalf: What Researchers Say and How Audiences Choose Why We (Usually) Don’t Have to Worry About Multiple Comparisons Visualization in Bayesian workflow Stan User’s Guide Bayesian Data Analysis Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan Data Analysis Using Regression and Multilevel/Hierarchical Models What works for whom?