Spatio-Temporal Models on the Basis of Innovation Processes and Application to Cancer Mortality Data
Loading...
Date
2000
Authors
Journal Title
Journal ISSN
Volume Title
Publisher
Universitätsbibliothek Dortmund
Abstract
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.
Description
Table of contents
Keywords
conditional autoregressive approach, innovation process, lattice data, ML-estimation, spatio-temporal linear model