Research on Integrated Time Series Analysis Softwares

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By the research in the previous fiscal years, we have developed a recursive filtering and smoothing algorithms for a general state space model which can be applied to diverse fields of time series modeling.Based on these results, in this year, we tested the developed program on various real data sets and made necessary modifications. We also did research on developing new models and more efficient algorithms. As a result of this research, based on the non-Gaussian state space model, a unified method fr analyzing time series with various characters such as the non-linearity, non-stationarity, non-Gaussianity, outliers and missing observations has been established. We also did research on the graphical display of the results of time series analysis and developed various programs for that purpose. In particular, by using the CALCOMP graphic libraries it becomes possible to use the graphical programs on various kinds of computers including mainframes and personal computers.As mentioned above, in this research a statistical model for handling time series with various character and a softrware for implementing the approach have been developed. Therefore, we believe that the most part of our purpose of this research has been achieved. However, more research is required to develop a user-friendly practical software.The papers and other publications produced concerning this research have been included in the report of this research project. A manual for the developed software is also available.