Reflections on Bayesian inference and Markov chain Monte Carlo

IF 1 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
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引用次数: 2

Abstract

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
CiteScore
1.40
自引率
0.00%
发文量
62
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.
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