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Research on the stability and robustness of seasonal adjustment procedure

季节调整程序的稳定性和鲁棒性研究

基本信息

批准号：
11695024
负责人：
TAMURA Yoshiyasu
金额：
$ 2.18万
依托单位：
THE INSTITUTE OF STATISTICAL MATHEMATICS
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (B)
财政年份：
1999
资助国家：
日本
起止时间：
1999 至 2001
项目状态：
已结题

项目摘要

General state-space models are applied to various types of problems in seasonal adj ustment. Especially, Monte Carlo filter, smoothing and self-organizing state-space model are found to be useful for stable and robust treatment of statistical seasonal adjustment. To put it precisely, new methods are developed for multiplicative type non-linear seasonal adjustment, for seasonal adjustment in small count data, and for automatic outlier detection in seasonal adjustment. Furthermore, model averaging type seasonal adjustment has been explored. In other words, we do not confine the seasonal model to a specific one but consider and monitor all the possible seasonal models, and realize prediction by weighting these models. On the other hand, as a generalization of time serics problem, removing intraday periodicity in high frequent financial data is considered via point process modeling by conditional intensity approach. It is shown that commonly employed method that use spline smoothing to estimate time-of-day function does not completely remove such intraday periodicity. In the final year of this research grant, an intemational symposium on statistical seasonal adjustment was held in Tokyo under the title 'Modeling Seasonality and Periodicity' on January 3 1 and February I, which ended in a great success. Newly developed software E-Decomp was released and distributed to the conference participants on free CD-ROM.

一般状态空间模型适用于季节调整中的各种类型的问题。特别是，蒙特卡洛滤波器、平滑和自组织状态空间模型被发现对于统计季节性调整的稳定和鲁棒处理非常有用。准确地说，开发了乘法型非线性季节调整、小计数数据季节调整、季节调整异常值自动检测等新方法。此外，还探索了模型平均型季节性调整。换句话说，我们并不将季节性模型局限于特定的一种，而是考虑并监控所有可能的季节性模型，并通过对这些模型进行加权来实现预测。另一方面，作为时间序列问题的推广，通过条件强度方法的点过程建模来考虑消除高频金融数据中的日内周期性。结果表明，常用的使用样条平滑来估计时间函数的方法并不能完全消除这种日内周期性。在这项研究资助的最后一年，1月3日1日和2月1日在东京举行了题为“季节性和周期性建模”的统计季节性调整国际研讨会，并取得了巨大成功。新开发的软件E-Decomp发布并以免费CD-ROM形式分发给与会者。