Theory of spatio-temporal data analysis and its applications to environmental data

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This research has conducted a proposition of nonstationary Fourier analysis of spatio-temporal data when observation points are irregularly spaced. Originally nonstatinary Fourier analysis was proposed for nonstationary time series analysis by local periodogram in order to identify temporal dependencies of time series models. Here we extend the method for time series to that for spatio-temporal data that makes it possible to identify local dependencies of spatial model parameters. The consistency of the estimators by the nonstationary Fourier methods has been proved. We have applied the methodology to land price data in Kanto area and examined nonstationary behaviors of land price data by the Fourier analysis.