Reflections on Bayesian inference and Markov chain Monte Carlo

被引：4
|
作者：
Craiu, Radu, V [1 ]
Gustafson, Paul [2 ]
Rosenthal, Jeffrey S. [1 ]
机构：
[1] Univ Toronto, Dept Stat Sci, Toronto, ON, Canada
[2] Univ British Columbia, Dept Stat, Vancouver, BC, Canada
来源：
CANADIAN JOURNAL OF STATISTICS-REVUE CANADIENNE DE STATISTIQUE | 2022年 / 50卷 / 04期
基金：
加拿大自然科学与工程研究理事会;
关键词：
Bayesian inference; Markov chain Monte Carlo; CONVERGENCE-RATES; PARALLEL; COMPUTATION; BOUNDS; COMPLEXITY; SAMPLER; MCMC;
D O I：
10.1002/cjs.11707
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：
Bayesian inference and Markov chain Monte Carlo methods are vigorous areas of statistical research. Here we reflect on some recent developments and future directions in these fields.
引用
收藏
页码：1213 / 1227
页数：15
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