| Research Abstract |
In this research project, I have treated the statistical consideration on the inference of spectral structure of the nonstationary time series, whose statistical share changes gradually over time. The project has been proceeded with the goals that 1)mathematical evaluation on the relationship between the speed in changing statistical structure and the accuracy in estimating nonstationary spectrem, and 2)the application of the concept of (1) to the aspect of data analysis
In this project, under the assumption that the nonstationary time series follows an oscillatory process and it has a nonstationary spectral density structure, some mathematical results on the errors in estimating the nonstationary spectrum were obtained, and they were presented in the conference of ISI (International Statistical Institute), in Apr.,2005. The presented method has the disadvantage, however, that it is not necessarily flexible for the practical application. So, we also developed a new methodology, which is available for the application in the practical aspect. In this project, as a case, we developed a space-time model based on the space-time data, including different speeds in changing structure, measured by an observation satellite. Furthermore, we could show that the statistical structure we proposed is valid to some extent, via evaluation of forecasting performance by applying this model. The paper has been published in IEEE Geoscience and Remote Sensing Letters.
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