Compatible Prior Distributions for DAG models

Guido Consonni, Alberto Roverato

Risultato della ricerca: Contributo in rivistaArticolo in rivistapeer review

11 Citazioni (Scopus)

Abstract

The application of certain Bayesian techniques, such as the Bayes factor and model averaging, requires the specification of prior distributions on the parameters of alternative models. We propose a new method for constructing compatible priors on the parameters of models nested in a given directed acyclic graph model, using a conditioning approach. We define a class of parameterizations that is consistent with the modular structure of the directed acyclic graph and derive a procedure, that is invariant within this class, which we name reference conditioning.
Lingua originaleEnglish
pagine (da-a)47-61
Numero di pagine15
RivistaJOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B STATISTICAL METHODOLOGY
Volume66
DOI
Stato di pubblicazionePubblicato - 2004

Keywords

  • Compatible prior
  • Directed acyclic graph

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