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

页码：1213 / 1227

页数：15

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