Reference priors for discrete graphical models

The combination of graphical models and reference analysis represents a powerful tool for Bayesian inference in highly multivariate settings. It is typically difficult to derive reference priors in complex problems. In this paper we present a suitable mixed parameterisation for a discrete decomposable graphical model and derive the corresponding reference prior.

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Year of publication:	2005
Authors:	Consonni, Guido ; Leucari, Valentina
Publisher:	Pavia : Università degli Studi di Pavia, Dipartimento di Economia Politica e Metodi Quantitativi (EPMQ)
Subject:	Bayes-Statistik \| Inferenzstatistik \| Decomposable model \| Fisher information matrix \| Mixed parameterisation \| Natural exponential family

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Series:	Quaderni di Dipartimento - EPMQ ; 181
Type of publication:	Book / Working Paper
Type of publication (narrower categories):	Working Paper
Language:	English
Other identifiers:	51219114X [GVK] hdl:10419/87114 [Handle]
Source:	EconStor

Persistent link: https://www.econbiz.de/10010326096