Tag Archives: mcmc

Why and how pseudo-marginal MCMC work for exact Bayesian inference

Posted on March 26, 2018 by Umberto P

I will describe a breakthrough strategy for “exact-approximate” Bayesian inference. The apparent contradiction in the terminology is due to the surprising result in Beaumont (2003) and Andrieu and Roberts (2009) where it is shown that plugging a non-negative and unbiased … Continue reading →

Posted in Uncategorized | Tagged Bayes, Bayesian inference, intractable likelihood, introduction, likelihood free, markov chain monte carlo, mcmc, Monte Carlo, particle marginal, particle MCMC, pseudo marginal, R, sequential Monte Carlo, software, tutorial | 3 Comments

Tips for coding a Metropolis-Hastings sampler

Posted on December 18, 2017 by Umberto P

I will suggest several tips, and discuss common beginner’s mistakes occuring when coding from scratch a Metropolis-Hastings algorithm. I am making this list from the top of my mind, so feel free to propose suggestions by commenting to this post. … Continue reading →

Posted in Uncategorized | Tagged beginner, coding, hastings, markov chain monte carlo, mcmc, metropolis, metropolis-hastings, mistakes, recommendations, tips | 15 Comments

Tag Archives: mcmc

Why and how pseudo-marginal MCMC work for exact Bayesian inference

Tips for coding a Metropolis-Hastings sampler

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