48 citations · 153 across the 26 of their papers we have counts for
4 papers · 1 filter
Nearly optimal Bayesian Shrinkage for High Dimensional Regression
Qifan Song, Faming Liang
During the past decade, shrinkage priors have received much attention in Bayesian analysis of high-dimensional data. This paper establishes the posterior consistency for high-dimen…
Weak Convergence Rates of Population versus Single-Chain Stochastic Approximation MCMC Algorithms
Qifan Song, Mingqi Wu, Faming Liang
In this paper, we establish the theory of weak convergence (toward a normal distribution) for both single-chain and population stochastic approximation MCMC algorithms. Based on th…
Trajectory averaging for stochastic approximation MCMC algorithms
Faming Liang
The subject of stochastic approximation was founded by Robbins and Monro [Ann. Math. Statist. 22 (1951) 400--407]. After five decades of continual development, it has developed int…
Improving SAMC using smoothing methods: Theory and applications to Bayesian model selection problems
Faming Liang
Stochastic approximation Monte Carlo (SAMC) has recently been proposed by Liang, Liu and Carroll [J. Amer. Statist. Assoc. 102 (2007) 305--320] as a general simulation and optimiza…