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5月30日,林蔚(首都经济贸易大学国际经济管理学院)
发布时间:2018-05-17   发布人:zs   点击数:91

报告人:林蔚,首都经济贸易大学国际经济管理学院

时间:5月30日(周三)下午1:30—3:00

地点:博学楼1227教室

题目: The RSVD Approach to Seasonal Adjustment

摘要:We propose a new seasonal adjustment approach based on the regularized singular value decomposition (RSVD) of the matrix obtained by reshaping the seasonal time series data. The method is flexible enough to capture two kinds of seasonality: the fixed seasonality that does not change over time and the time-varying seasonality that varies from one season to another. The new method is capable of capturing multiple seasonal patterns and how they change over time. By assuming the time-varying seasonal patterns change smoothly over time, the RSVD imposes a roughness penalty to effectively extract the time-varying seasonality. The proposed methods is applicable to the seasonal time series data with a stationary or difference stationary non-seasonal component. Our proposed RSVD approach is general enough to handle several irregular cases: (i) the existence of abrupt breaks in seasonality, (ii) seasonal time series with mixed frequencies, and (iii) the existence of multiple types of seasonality. Our proposed method compares favorably with the state-of-art X-13ARIMA-SEATS program on both simulated and real data examples.

报告人简介:林蔚副教授,任职于首都经济贸易大学国际经济管理学院。主要研究领域包括时间序列分析和非参数计量经济学。他在Journal of Econometrics, Journal of Business and Economic Statistics等国际学术期刊上发表学术论文数篇,主持并参与两项国家自科基金。

 

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