Evaluating parallelisable Markov chain Monte Carlo algorithms via waste-recycling
主 题: Evaluating parallelisable Markov chain Monte Carlo algorithms via waste-recycling
报告人: Prof. Liu Jun (Harvard University)
时 间: 2016-12-17 14：00-14：30
地 点: 理科一号楼 1114
Parallelisable Markov chain Monte Carlo algorithms generate multiple proposals and parallelise the evaluations of the likelihood functions on different cores at each iteration. Here we give simple-to-use criteria for evaluations and comparisons of general (parallelisable) waste-recycling Markov chain Monte Carlo algorithms. We give a formula for the effective sample size of multiple-proposal algorithms, which is easy to implement using moment estimators.
(Joint work with Espen Bernton, Yang Chen, Shihao Yang, and Neil Shephard)
