基于切片Gibbs抽样算法的空间误差模型的贝叶斯参数估计

doi:10.6040/j.issn.1671-9352.0.2023.474

《山东大学学报(理学版)》 ›› 2025, Vol. 60 ›› Issue (3): 116-126.doi: 10.6040/j.issn.1671-9352.0.2023.474

• • 上一篇

基于切片Gibbs抽样算法的空间误差模型的贝叶斯参数估计

李澳归¹,赵远英^2,3*

1.贵州大学数学与统计学院, 贵州贵阳 550025;2.贵阳学院理学院, 贵州贵阳 550005;3.贵州交通职业大学轨道交通工程系, 贵州贵阳 551400

发布日期:2025-03-10
通讯作者: 赵远英(1981— ),男,教授,硕士生导师,博士,研究方向为应用统计. E-mail:zhaoyuanying_@126.com
作者简介:李澳归(1999— ),男,硕士研究生,研究方向为概率论与数理统计. E-mail:lagjs123@163.com*通信作者:赵远英(1981— ),男,教授,硕士生导师,博士,研究方向为应用统计. E-mail:zhaoyuanying_@126.com
基金资助:
国家自然科学基金资助项目(12161014);贵州省省级科技计划项目(黔科合支撑［2023］一般139)2018年度贵州省高层次创新型人才项目阶段性成果

Bayesian parametric estimations for spatial error models based on slice-Gibbs sampling

LI Aogui¹, ZHAO Yuanying^2,3*

1. College of Mathematics and Statistic, Guizhou University, Guiyang 550025, Guizhou, China;
2. College of Science, Guiyang University, Guiyang 550005, Guizhou, China;
3. Department of Railway Engineering, Guizhou Communications Polytechnic University, Guiyang 551400, Guizhou, China

Published:2025-03-10

摘要/Abstract

摘要： 提出一种切片Gibbs抽样的马尔可夫链蒙特卡罗(Markov chain Monte Carlo, MCMC)算法来计算空间误差模型未知参数的联合贝叶斯估计,通过2个模拟仿真说明提出的贝叶斯估计方法的有效性与切片Gibbs抽样算法的优势,实证分析说明模型和提出的贝叶斯估计方法的有效性。

关键词: 贝叶斯估计, Gibbs抽样, 切片抽样, 空间误差模型

Abstract: A Markov chain Monte Carlo(MCMC)technique called the slice-Gibbs sampling algorithm is proposed to calculate joints Bayesian estimations of unknown parameters for spatial error models, the proposed algorithm and Bayesian approach are illustrated by two simulation studies, the model and methodology are demonstrated by a real example.

Key words: Bayesian estimation, Gibbs sampling, slice sampling, spatial error model

中图分类号:

O212.8

李澳归,赵远英. 基于切片Gibbs抽样算法的空间误差模型的贝叶斯参数估计[J]. 《山东大学学报(理学版)》, 2025, 60(3): 116-126.

LI Aogui, ZHAO Yuanying. Bayesian parametric estimations for spatial error models based on slice-Gibbs sampling[J]. JOURNAL OF SHANDONG UNIVERSITY(NATURAL SCIENCE), 2025, 60(3): 116-126.

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基于切片Gibbs抽样算法的空间误差模型的贝叶斯参数估计

Bayesian parametric estimations for spatial error models based on slice-Gibbs sampling

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