Undirected Structural Markov Property for Bayesian Model Determination

Autor:	Xiong Kang, Yingying Hu, Yi Sun
Jazyk:	angličtina
Rok vydání:	2023
Předmět:	graphical model structural Markov law Bayesian inference model determination Mathematics QA1-939
Zdroj:	Mathematics, Vol 11, Iss 7, p 1590 (2023)
Druh dokumentu:	article
ISSN:	2227-7390
DOI:	10.3390/math11071590
Popis:	This paper generalizes the structural Markov properties for undirected decomposable graphs to arbitrary ones. This helps us to exploit the conditional independence properties of joint prior laws to analyze and compare multiple graphical structures, while being able to take advantage of the common conditional independence constraints. This work provides a theoretical support for full Bayesian posterior updating about the structure of a graph using data from a certain distribution. We further investigate the ratio of graph law so as to simplify the acceptance probability of the Metropolis–Hastings sampling algorithms.
Databáze:	Directory of Open Access Journals
Externí odkaz:	https://doaj.org/article/aadadb697da54272a8db1cab492aeb3c Zobrazit plný text záznamu View record in DOAJ Plný text ve formátu PDF Plný text ve formátu HTML
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