KERNEL ESTIMATORS OF ASYMPTOTIC VARIANCE FOR ADAPTIVE MARKOV CHAIN MONTE CARLO

被引：12
|
作者：
Atchade, Yves F. [1 ]
机构：
[1] Univ Michigan, Dept Stat, Ann Arbor, MI 48109 USA
来源：
ANNALS OF STATISTICS | 2011年 / 39卷 / 02期
关键词：
Adaptive Markov chain Monte Carlo; kernel estimators of asymptotic variance; CONSISTENCY; ERGODICITY; HETEROSKEDASTICITY;
D O I：
10.1214/10-AOS828
中图分类号：
O21 [概率论与数理统计]; C8 [统计学];
学科分类号：
020208 ; 070103 ; 0714 ;
摘要：
We study the asymptotic behavior of kernel estimators of asymptotic variances (or long-run variances) for a class of adaptive Markov chains. The convergence is studied both in L-P and almost surely. The results also apply to Markov chains and improve on the existing literature by imposing weaker conditions. We illustrate the results with applications to the GARCH(1, 1) Markov model and to an adaptive MCMC algorithm for Bayesian logistic regression.
引用
收藏
页码：990 / 1011
页数：22
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