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Combining Euclidean and composite likelihood for binary spatial data estimation
- Bevilacqua, Moreno, Crudu, Federico, Porcu, Emilio
- Stochastic environmental research and risk assessment 2015 v.29 no.2 pp. 335-346
- estimation, mortality, neoplasms, probability analysis, spatial data
- In this paper we propose a blockwise Euclidean likelihood method for the estimation of a spatial binary field obtained by thresholding a latent Gaussian random field. The moment conditions used in the Euclidean likelihood estimator derive from the score of the composite likelihood based on marginal pairs. A feature of this approach is that it is possible to obtain computational benefits with respect to the pairwise likelihood depending on the choice of the spatial blocks. A simulation study and an analysis on cancer mortality data compares the two methods in terms of statistical and computational efficiency. We also study the asymptotic properties of the proposed estimator.