Exact convergence analysis of the independent Metropolis-Hastings algorithms

被引:3
|
作者
Wang, Guanyang [1 ]
机构
[1] Rutgers State Univ, Dept Stat, Piscataway, NJ 08854 USA
关键词
Independent Metropolis-Hastings; Markov chain Monte Carlo; exact convergence rate; MARKOV-CHAINS; DISTRIBUTIONS; MINORIZATION; RATES;
D O I
10.3150/21-BEJ1409
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
A well-known difficult problem regarding Metropolis-Hastings algorithms is to get sharp bounds on their convergence rates. Moreover, a fundamental but often overlooked problem in Markov chain theory is to study the convergence rates for different initializations. In this paper, we study the two issues mentioned above of the Independent Metropolis-Hastings (IMH) algorithms on both general and discrete state spaces. We derive the exact convergence rate and prove that the IMH algorithm's different deterministic initializations have the same convergence rate. We get the exact convergence speed for IMH algorithms on general state spaces.
引用
收藏
页码:2012 / 2033
页数:22
相关论文
共 50 条
  • [31] Efficient parallelisation of Metropolis-Hastings algorithms using a prefetching approach
    Strid, Ingvar
    COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2010, 54 (11) : 2814 - 2835
  • [32] A note on acceptance rate criteria for CLTs for Metropolis-Hastings algorithms
    Roberts, GO
    JOURNAL OF APPLIED PROBABILITY, 1999, 36 (04) : 1210 - 1217
  • [33] Kernel Adaptive Metropolis-Hastings
    Sejdinovic, Dino
    Strathmann, Heiko
    Garcia, Maria Lomeli
    Andrieu, Christophe
    Gretton, Arthur
    INTERNATIONAL CONFERENCE ON MACHINE LEARNING, VOL 32 (CYCLE 2), 2014, 32 : 1665 - 1673
  • [34] On adaptive Metropolis-Hastings methods
    Griffin, Jim E.
    Walker, Stephen G.
    STATISTICS AND COMPUTING, 2013, 23 (01) : 123 - 134
  • [35] On an adaptive version of the Metropolis-Hastings algorithm with independent proposal distribution
    Gåsemyr, J
    SCANDINAVIAN JOURNAL OF STATISTICS, 2003, 30 (01) : 159 - 173
  • [36] Scaling limits for the transient phase of local Metropolis-Hastings algorithms
    Christensen, OF
    Roberts, GO
    Rosenthal, JS
    JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY, 2005, 67 : 253 - 268
  • [37] A history of the Metropolis-Hastings algorithm
    Hitchcock, DB
    AMERICAN STATISTICIAN, 2003, 57 (04): : 254 - 257
  • [38] Variance reduction of estimators arising from Metropolis-Hastings algorithms
    Iliopoulos, George
    Malefaki, Sonia
    STATISTICS AND COMPUTING, 2013, 23 (05) : 577 - 587
  • [39] Log-concave sampling: Metropolis-Hastings algorithms are fast
    Dwivedi, Raaz
    Chen, Yuansi
    Wainwright, Martin J.
    Yu, Bin
    Journal of Machine Learning Research, 2019, 20
  • [40] UNDERSTANDING THE METROPOLIS-HASTINGS ALGORITHM
    CHIB, S
    GREENBERG, E
    AMERICAN STATISTICIAN, 1995, 49 (04): : 327 - 335