Statistical analysis of locally stationary processes

被引：0

作者：

Ferreira, Guillermo ^{[1
]}

Olea, Ricardo ^{[2
]}

Palma, Wilfredo ^{[2
]}

机构：

[1] Univ Concepci, Dept Stat, Concepcion, Chile

[2] Pontificia Univ Catolica Chile, Dept Stat, Santiago, Chile

来源：

CHILEAN JOURNAL OF STATISTICS | 2013年 / 4卷 / 02期

关键词：

Kalman filter; State space system; Nonstationarity; Long-range dependence; Local stationarity; Time-varying models;

D O I：

暂无

中图分类号：

O21 [概率论与数理统计]; C8 [统计学];

学科分类号：

020208 ; 070103 ; 0714 ;

摘要：

This paper provides an overview of locally stationary processes, a helpful methodology for handling nonstationary time series. These techniques allow for the smooth evolution of the model parameters. This work reviews estimation and predictions techniques, illustrating the application of these methods to real-life data examples. These examples show that the locally stationary methods provide a useful theoretical and practical framework for the statistical analysis of nonstationary time series data.

引用

页码：133 / 149

页数：17

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