This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Nieto-Barajas, L. E Search for Related Content Social Bookmarking                         What's this?

A Markov gamma random field for modelling disease mapping data

Luis E Nieto-Barajas is at Department of Statistics, ITAM, Rio Hondo 1, Tizapan San Angel, 01000 Mexico D.F., Mexico. E-mail: lnieto{at}itam.mx

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.

Key Words: Bayes nonparametrics • correlated gamma process • discrete Markov gamma process • disease mapping • latent variables

Statistical Modelling, Vol. 8, No. 1, 97-114 (2008)
DOI: 10.1177/1471082X0700800107


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?