关于贝叶斯推理和马尔可夫链蒙特卡罗的思考

IF 0.8 4区数学 Q3 STATISTICS & PROBABILITY

Canadian Journal of Statistics-Revue Canadienne De Statistique Pub Date : 2022-07-04 DOI:10.1002/cjs.11707

Radu V. Craiu, Paul Gustafson, Jeffrey S. Rosenthal

引用次数: 2

摘要

贝叶斯推理和马尔可夫链蒙特卡罗方法是统计学研究的热点。在这里，我们回顾一下这些领域的一些最新发展和未来方向。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Reflections on Bayesian inference and Markov chain Monte Carlo

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.

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来源期刊

Canadian Journal of Statistics-Revue Canadienne De Statistique 数学-统计学与概率论

CiteScore

1.40

自引率

0.00%

发文量

审稿时长

>12 weeks

期刊介绍： The Canadian Journal of Statistics is the official journal of the Statistical Society of Canada. It has a reputation internationally as an excellent journal. The editorial board is comprised of statistical scientists with applied, computational, methodological, theoretical and probabilistic interests. Their role is to ensure that the journal continues to provide an international forum for the discipline of Statistics. The journal seeks papers making broad points of interest to many readers, whereas papers making important points of more specific interest are better placed in more specialized journals. The levels of innovation and impact are key in the evaluation of submitted manuscripts.