The chi-square coding test for nested Markov random field hypotheses

Cécile Hardouin (1) , Xavier Guyon (1)

1 SAMOS - Statistique Appliquée et MOdélisation Stochastique

Let Y be a Markov random foeld on S parametrized via its local conditional specifications. We study consistency of coding and pseudo-likelihood estimators. Then we obtain conditional asymptotic normality for the coding estimator and deduce that the difference of coding statistic for two nested hypotheses is, unconditionally, a chi-square. For these results, we do not need regularity of the lattice, translation invariance for the specification or weak dependence for the field.

Mots clés: Conditional specification; Markov random field; coding and pseudo-likelihood estimators; difference of coding tests

Domaines: Statistiques [math.ST]

Cécile Hardouin, Xavier Guyon. The chi-square coding test for nested Markov random field hypotheses. 1992, pp.165-176. ⟨hal-00110636⟩