Generating Independent Replicates Directly from the Posterior Distribution for a Class of Spatial Hierarchical Models

IF 1.4 2区数学 Q2 STATISTICS & PROBABILITY

Journal of Computational and Graphical Statistics Pub Date : 2024-06-11 DOI:10.1080/10618600.2024.2365728

Jonathan R. Bradley, Madelyn Clinch

引用次数: 0

Abstract

Markov chain Monte Carlo (MCMC) allows one to generate dependent replicates from a posterior distribution for effectively any Bayesian hierarchical model. However, MCMC can produce a significant co...

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直接从一类空间层次模型的后验分布生成独立副本

马尔科夫链蒙特卡洛（MCMC）允许人们从任何贝叶斯层次模型的后验分布中生成依赖性副本。然而，MCMC 可能会产生显著的...

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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.