期刊
JOURNAL OF COMPUTATIONAL AND GRAPHICAL STATISTICS
卷 18, 期 2, 页码 349-367出版社
AMER STATISTICAL ASSOC
DOI: 10.1198/jcgs.2009.06134
关键词
Adaption; Convergence; Hierarchical models; Markov chain Monte Carlo; Metropolis algorithm; Metropolis-within-Gibbs; Nonconjugate priors; Non-Markovian
资金
- NSERC of Canada
- Engineering and Physical Sciences Research Council [EP/D002060/1] Funding Source: researchfish
We investigate the use of adaptive MCMC algorithms to automatically tune the Markov chain parameters during a run. Examples include the Adaptive Metropolis (AM) multivariate algorithm of Haario, Saksman, and Tamminen (2001), Metropolis-within-Gibbs algorithms for nonconjugate hierarchical models, regionally adjusted Metropolis algorithms, and logarithmic scalings. Computer simulations indicate that the algorithms perform very well compared to nonadaptive algorithms, even in high dimension.
作者
我是这篇论文的作者
点击您的名字以认领此论文并将其添加到您的个人资料中。
推荐
暂无数据
分享论文
