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Semiparametric modelling of spatial binary observations

Dipartimento di Statistica, Probabilità e Statistiche Applicate, Università degli Studi ‘La Sapienza’ di Roma, Italy, Marco.Alfo{at}uniroma1.it

Paolo Postiglione

Dipartimento di Scienze, Università degli Studi ‘G. d’Annunzio’ di Chieti, Italy

In the past decade various attempts have been made to extend standard random effects models to the analysis of spatial observations. This extension is a source of theoretical difficulty due to the multidirectional dependence among nearest observations; much of the previous work was based on parametric assumptions about the random effects distribution. To avoid any restriction, we propose a conditional model for spatial binary responses, without assuming a parametric distribution for the random effects. The model parameters are estimated using the EM algorithm for nonparametric maximum likelihood estimation of a mixing distribution. To illustrate the proposed approach, the model is applied to a remote sensed image of the Nebrodi Mountains (Italy).

Key Words: autologistic model • nonparametric maximum likelihood • random effects • spatial binary responses

Statistical Modelling, Vol. 2, No. 2, 123-137 (2002)
DOI: 10.1191/1471082x02st023oa


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