We propose an extension of graphical log-linear models to allow for symmetry constraints on some interaction parameters that represent homologous factors. The conditional independence structure of such quasi-symmetric (QS) graphical models is described by an undirected graph with coloured edges, in which a particular colour corresponds to a set of equality constraints on a set of parameters. Unlike standard QS models, the proposed models apply with contingency tables for which only some variables or sets of the variables have the same categories. We study the graphical properties of such models, including conditions for decomposition of model parameters and of maximum likelihood estimates.

Quasi-Symmetric Graphical Log-Linear Models / A.Gottard; G.M.Marchetti; A.Agresti. - In: SCANDINAVIAN JOURNAL OF STATISTICS. - ISSN 0303-6898. - STAMPA. - 38(2011), pp. 447-465. [10.1111/j.1467-9469.2010.00713.x]

Quasi-Symmetric Graphical Log-Linear Models

GOTTARD, ANNA
;
MARCHETTI, GIOVANNI MARIA;
2011

Abstract

We propose an extension of graphical log-linear models to allow for symmetry constraints on some interaction parameters that represent homologous factors. The conditional independence structure of such quasi-symmetric (QS) graphical models is described by an undirected graph with coloured edges, in which a particular colour corresponds to a set of equality constraints on a set of parameters. Unlike standard QS models, the proposed models apply with contingency tables for which only some variables or sets of the variables have the same categories. We study the graphical properties of such models, including conditions for decomposition of model parameters and of maximum likelihood estimates.
38
447
465
A.Gottard; G.M.Marchetti; A.Agresti
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/2158/394942
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