Spatio-Temporal Models on the Basis of Innovation Processes and Application to Cancer Mortality Data

Schach, Ulrike2004-12-062004-12-062000http://hdl.handle.net/2003/502110.17877/DE290R-15113The 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.enUniversitätsbibliothek Dortmundconditional autoregressive approachinnovation processlattice dataML-estimationspatio-temporal linear model310Spatio-Temporal Models on the Basis of Innovation Processes and Application to Cancer Mortality Datareport