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.
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Bilancia, M., Pollice, A. (2004). A Spatial Clustering Hierarchical Model for Disease Mapping. In: Bock, HH., Chiodi, M., Mineo, A. (eds) Advances in Multivariate Data Analysis. Studies in Classification, Data Analysis, and Knowledge Organization. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-17111-6_17
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DOI: https://doi.org/10.1007/978-3-642-17111-6_17
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