In search of lost mixing time: adaptive Markov chain Monte Carlo schemes for Bayesian variable selection with very large p
寻找失落的混合时间：超高维贝叶斯变量选择的自适应 MCMC
Summary The availability of datasets with large numbers of variables is rapidly increasing. The effective application of Bayesian variable selection methods for regression with these datasets has proved difficult since available Markov chain Monte Carlo methods do not perform well in typical problem sizes of interest. We propose new adaptive Markov chain Monte Carlo algorithms to address this shortcoming. The adaptive design of these algorithms exploits the observation that…