Computational methods for fast Bayesian model assessment via calibrated posterior p-values

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-07-11 DOI:10.1080/10618600.2024.2374585

Sally Paganin, Perry de Valpine

引用次数: 0

Abstract

Posterior predictive p-values (ppps) have become popular tools for Bayesian model assessment, being general-purpose and easy to use. However, interpretation can be difficult because their distribut...

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通过校准后p值快速评估贝叶斯模型的计算方法

后验预测 p 值（pps）因其通用性和易用性，已成为贝叶斯模型评估的常用工具。然而，由于其分布不均，解释起来可能很困难。

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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来源期刊

Journal of Computational and Graphical Statistics 数学-统计学与概率论

CiteScore

3.50

自引率

8.30%

发文量

153

审稿时长

>12 weeks

期刊介绍： The Journal of Computational and Graphical Statistics (JCGS) presents the very latest techniques on improving and extending the use of computational and graphical methods in statistics and data analysis. Established in 1992, this journal contains cutting-edge research, data, surveys, and more on numerical graphical displays and methods, and perception. Articles are written for readers who have a strong background in statistics but are not necessarily experts in computing. Published in March, June, September, and December.