355 articles – 411 references  [version française]
HAL: hal-00641487, version 1

Detailed view  Export this paper
Evaluating statistic appropriateness for Bayesian model choice
Jean-michel MARIN 1, Natesh Pillai 2, Christian Robert 3, 4, Judith Rousseau 3, 4
(2011)

The choice of the summary statistics in Bayesian inference and in particular in ABC is paramount to produce a valid outcome. We examine necessary and sufficient conditions on those statistics for a corresponding Bayes factor to be convergent. The conditions thus obtained are then usable in ABC settings to determine which summary statistics are appropriate, following a standard Monte Carlo validation.
1:  Institut de Mathématiques et de Modélisation de Montpellier (I3M)
CNRS : UMR5149 – Université Montpellier II - Sciences et techniques
2:  Department of Statistics
University of Harvard
3:  CEntre de REcherches en MAthématiques de la DEcision (CEREMADE)
CNRS : UMR7534 – Université Paris IX - Paris Dauphine
4:  Centre de Recherche en Économie et Statistique (CREST)
INSEE – École Nationale de la Statistique et de l'Administration Économique
Mathematics/Statistics

Statistics/Statistics Theory
Attached file list to this document: 
PDF
MPRR11.pdf(275.2 KB)