Characterization of convolution splitting graphical models - Inria - Institut national de recherche en sciences et technologies du numérique
Journal Articles Statistics and Probability Letters Year : 2017

Characterization of convolution splitting graphical models

Abstract

We aim at characterizing graphical models for convolution splitting distributions. Only marginal independence have been studied through the well-known Rao–Rubin condition. We generalize this condition for conditional independence and deduce the desired characterizations.
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hal-01286173 , version 1 (10-03-2016)

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Jean Peyhardi, Pierre Fernique. Characterization of convolution splitting graphical models. Statistics and Probability Letters, 2017, 126, ⟨10.1016/j.spl.2017.02.018⟩. ⟨hal-01286173⟩
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