Research on a systematic analysis of information on GPS array data

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We analyzed GPS data at 1,000 stations covering all over Japan for two years frorn 1996 through 1997. Specifically, an detailed investigation on data sets in terrns of data quality limited us to use 614 data points among them. We performed a Bayesian smoothing procedure in time-spatial domain which allows us to extract the mean structure automatically, and tried to model the mean structure based on the result obtained. Actually, we applied the non-parametric smoothing based on the Bayesian approach and conducted the residual analysis alternatively in each of time- and spatial domains. Finally we decomposed the variations of GPS data for each station into three components : time-dependent, spatial-dependent, and other components. We presented the result at the international meeting, and obtain the positive response from the attendants.