A NEW PRIOR FOR DISCRETE DAG MODELS WITH A RESTRICTED SET OF DIRECTIONS
成果类型:
Article
署名作者:
Massam, Helene; Wesolowski, Jacek
署名单位:
York University - Canada; Warsaw University of Technology
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
DOI:
10.1214/15-AOS1396
发表日期:
2016
页码:
1010-1037
关键词:
dirichlet distribution
neutralities
摘要:
In this paper, we first develop a new family of conjugate prior distributions for the cell probability parameters of discrete graphical models Markov with respect to a set P of moral directed acyclic graphs with skeleton a given decomposable graph G. This family, which we call the P-Dirichlet, is a generalization of the hyper Dirichlet given in [Ann. Statist. 21 (1993) 12721317]: it keeps the directed strong hyper Markov property for every DAG in P but increases the flexibility in the choice of its parameters, that is, the hyper parameters. Our second contribution is a characterization of the P-Dirichlet, which yields, as a corollary, a characterization of the hyper Dirichlet and a characterization of the Dirichlet also. Like the characterization of the Dirichlet given in [Ann. Statist. 25 (1997) 1344-1369], our characterization of the P-Dirichlet is based on local and global independence of the probability parameters and also a separability property explicitly defined here but implicitly used in that paper through the choice of two particular DAGs. Another advantage of our approach is that we need not make the assumption of the existence of a positive density function. We use the method of moments for our proofs.