Publications des agents du Cirad


Prediction of a multivariate spatial random field with continuous, count and ordianl outcomes

Chagneau P., Mortier F., Picard N., Bacro J.N.. 2008. In : Eds by Julián M. Ortiz, Xavier Emery. GEOSTATS 2008 : 8th International Geostatistics Congress, Santiago, Chili, 1-5 December 2008. Santiago : GECAMIN, p. 479-488. International Geostatistics Congress. 8, 2008-12-01/2008-12-05, Santiago (Chili).

As most georeferenced data sets are multivariate and concern variables of different kinds, spatial mapping methods must be able to deal with such data. The main difficulties are the prediction of non-Gaussian variables and the dependence modelling between processes. The aim of this paper is to present a new approach that permits simultaneous modelling of Gaussian, count and ordinal spatial processes. We consider a hierarchical model implemented within a Bayesian framework. The method used for Gaussian and count variables is based on the generalized linear model. Ordinal variable is taken into account through a generalization of the ordinal probit model. We use the moving average approach of Ver Hoef and Barry to model the dependencies between the processes.

Mots-clés : modèle mathématique

Documents associés

Communication de congrès

Agents Cirad, auteurs de cette publication :