Discussion on the paper by Brooks, Giudici and Roberts
对 Brooks、Giudici 与 Roberts 论文的讨论
This paper aims to develop general strategies for improving jumps between models in reversible jump Markov chain Monte Carlo (MCMC) algorithms, which is quite an important and timely goal. Indeed, in practical implementations of the method, we usually find that the choice of proposals is paramount: in many cases, the ‘natural choice’ leads to a zero acceptance probability and the construction of well-tuned moves is often quite costly. Given that the reversible jump MCMC…