In this paper a finite mixture model with a specific weights for each observation is introduced. The logistic transformation of these weights is modelled through a markovian field, with space autocorrelations of Gaussian type. This specification is particularly useful for desease mapping issues: some implementation difficulties are shortly discussed, together with the problem of the choice of the mixture's components number.
A spatial clustering hierarchical model for disease mapping
BILANCIA, Massimo;POLLICE, Alessio
2004-01-01
Abstract
In this paper a finite mixture model with a specific weights for each observation is introduced. The logistic transformation of these weights is modelled through a markovian field, with space autocorrelations of Gaussian type. This specification is particularly useful for desease mapping issues: some implementation difficulties are shortly discussed, together with the problem of the choice of the mixture's components number.File in questo prodotto:
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