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- W1983059681 abstract "Motivated by the modelling of non-Gaussian data or positively correlated data on a lattice, extensions of Besag's automodels to exponential families with multi-dimensional parameters have been proposed recently. We provide a multiple-parameter analogue of Besag's one-dimensional result that gives the necessary form of the exponential families for the Markov random field's conditional distributions. We propose estimation of parameters by maximum pseudolikelihood and give a proof of the consistency of the estimators for the multi-parameter automodel. The methodology is illustrated with examples, in particular the building of a cooperative system with beta conditional distributions. We also indicate future applications of these models to the analysis of mixed-state spatial data." @default.
- W1983059681 created "2016-06-24" @default.
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- W1983059681 date "2008-02-04" @default.
- W1983059681 modified "2023-09-30" @default.
- W1983059681 title "Multi-parameter automodels and their applications" @default.
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- W1983059681 doi "https://doi.org/10.1093/biomet/asn016" @default.
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