Articles by AO

Efficient MCMC with Caching

March 2, 2019 | AO

This post is part of a running series on Bayesian MCMC tutorials. For updates, follow @StableMarkets. Metropolis Review Metropolis-Hastings is an MCMC algorithm for drawing samples from a distribution known up to a constant of proportionality, $latex p(\theta | y) \propto p(y|\theta)p(\theta)$. Very briefly, the algorithm ... [Read more...]

Bayesian Inference with Backfitting MCMC

May 2, 2018 | AO

Previous posts in this series on MCMC samplers for Bayesian inference (in order of publication): Bayesian Simple Linear Regression with Gibbs Sampling in R Blocked Gibbs Sampling in R for Bayesian Multiple Linear Regression Metropolis-in-Gibbs Sampling... [Read more...]

Speeding up Metropolis-Hastings with Rcpp

March 16, 2018 | AO

Previous posts in this series on MCMC samplers for Bayesian inference (in order of publication): Bayesian Simple Linear Regression with Gibbs Sampling in R Blocked Gibbs Sampling in R for Bayesian Multiple Linear Regression Metropolis-in-Gibbs Sampling and Runtime Analysis with Profviz The code for all of these posts can be ... [Read more...]

Metropolis-in-Gibbs Sampling and Runtime Analysis with Profviz

November 7, 2017 | AO

First off, here are the previous posts in my Bayesian sampling series: Bayesian Simple Linear Regression with Gibbs Sampling in R Blocked Gibbs Sampling in R for Bayesian Multiple Linear Regression In the first post, I illustrated Gibbs Sampling - an algorithm for getting draws from a posterior when conditional ... [Read more...]

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