Spatio-temporal models on the basis of innovation processes and application to cancer mortality data

Ulrike Schach

The aim of this paper is to find a modeling approach for spatially and temporally structured data. The spatial distribution is considered to form an irregular lattice with a specified definition of neighborhood. Additional to the spatial component, a temporal autoregressive parameter, and a time trend are modeled within a multivariates Markov process. This Markov process can be expressed on the basis of an innovation process, which allows for statistical inference on various parameters.

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Year of publication:	2000
Authors:	Schach, Ulrike
Publisher:	Dortmund : SFB 475, Universität Dortmund
Subject:	Lattice data \| conditional autoregressive approach \| spatio-temporal linear model \| innovation process \| ML-estimation \| Innovation \| Theorie \| Theory \| Krebskrankheit \| Cancer \| Sterblichkeit \| Mortality \| Schätzung \| Estimation \| Innovationsmanagement \| Innovation management