JSTOR Daily

Adaptive Markov Chain Monte Carlo for Bayesian Variable Selection

We describe adaptive Markov chain Monte Carlo (MCMC) methods for sampling posterior distributions arising from Bayesian variable selection problems. Point-mass mixture priors are commonly used in ...
JSTOR Daily

Evaluating the Performance of a Block Updating MCMC Sampler in a Simple Genetic Application

Journal of Agricultural, Biological, and Environmental Statistics, Vol. 12, No. 2 (Jun., 2007), pp. 272-299 (28 pages) Markov chain Monte Carlo (MCMC) methods have provided an enormous break-through ...
Nature

Markov Chain Monte Carlo Methods

Markov Chain Monte Carlo (MCMC) methods have become indispensable in contemporary statistical science, enabling researchers to approximate complex probability distributions that are otherwise ...
lse

Bayesian Inference

This course is available on the BSc in Actuarial Science, BSc in Actuarial Science (with a Placement Year), BSc in Data Science, BSc in Mathematics with Data Science, BSc in Mathematics with Economics ...