2022年的近似交换性和de Finetti先验

IF 0.8 4区数学 Q3 STATISTICS & PROBABILITY

Scandinavian Journal of Statistics Pub Date : 2022-08-29 DOI:10.1111/sjos.12609

P. Diaconis

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引用次数: 4

摘要

这是一篇综述论文，从de Finetti关于部分可交换性的工作开始，继续他的近似可交换性方法，然后是他在非标准情况下分配信息先验的（令人惊讶的）方法。Gerencsér和Ottolini关于获得收敛率诚实界的工作综述补充了马尔可夫链蒙特卡罗方法得出结论的最新进展。本文最后提出了一种将经典渐近性与蒙特卡罗相结合的推测方法。这保证了真正的速度，并为理论和计算如何相互作用提供了一个很好的例子。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Approximate exchangeability and de Finetti priors in 2022

This is a review paper, beginning with de Finetti's work on partial exchangeability, continuing with his approach to approximate exchangeability, and then his (surprising) approach to assigning informative priors in nonstandard situations. Recent progress on Markov chain Monte Carlo methods for drawing conclusions is supplemented by a review of work by Gerencsér and Ottolini on getting honest bounds for rates of convergence. The paper concludes with a speculative approach to combining classical asymptotics with Monte Carlo. This promises real speed‐ups and makes a nice example of how theory and computation can interact.

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来源期刊

Scandinavian Journal of Statistics 数学-统计学与概率论

CiteScore

1.80

自引率

0.00%

发文量

审稿时长

6-12 weeks

期刊介绍： The Scandinavian Journal of Statistics is internationally recognised as one of the leading statistical journals in the world. It was founded in 1974 by four Scandinavian statistical societies. Today more than eighty per cent of the manuscripts are submitted from outside Scandinavia. It is an international journal devoted to reporting significant and innovative original contributions to statistical methodology, both theory and applications. The journal specializes in statistical modelling showing particular appreciation of the underlying substantive research problems. The emergence of specialized methods for analysing longitudinal and spatial data is just one example of an area of important methodological development in which the Scandinavian Journal of Statistics has a particular niche.