  The purpose of this paper is to extend standard finite mixture models in the
context of multinomial mixtures for spatial data, in order to cluster
geographical units according to demographic characteristics. The spatial
information is incorporated on the model through the mixing probabilities of
each component. To be more specific, a Gibbs distribution is assumed for prior
probabilities. In this way, assignment of each observation is affected by
neighbors' cluster and spatial dependence is included in the model. Estimation
is based on a modified EM algorithm which is enriched by an extra, initial step
for approximating the field. The simulated field algorithm is used in this
initial step. The presented model will be used for clustering municipalities of
Attica with respect to age distribution of residents.
