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• W2092544900 abstract "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." @default.
• W2092544900 created "2016-06-24" @default.
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• W2092544900 date "2014-08-19" @default.
• W2092544900 modified "2023-10-16" @default.
• W2092544900 title "Combining Euclidean and composite likelihood for binary spatial data estimation" @default.
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• W2092544900 doi "https://doi.org/10.1007/s00477-014-0938-8" @default.
• W2092544900 hasPublicationYear "2014" @default.
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