Statistical Modelling 8 (2008), 97–114

A Markov gamma random field for modelling disease mapping data

Luis E Nieto-Barajas
Department of Statistics,
ITAM,
Rio Hondo 1,
Tizapan San Angel, 01000 Mexico D.F.
Mexico. eMail: lnieto@itam.mx

Abstract:

In this paper we introduce a Markov gamma random field prior for modelling relative risks in disease mapping data. This prior process allows for a different dependence effect with different neighbours. We describe the properties of the prior process and derive posterior distributions. The model is extended to cope with covariates and a data set of respiratory infections of children in Mexico is used as an illustration.

Keywords:

Bayes nonparametrics; correlated gamma process; discrete Markov gamma process; disease mapping; latent variables
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