Fitting time series models to nonstationary processes

被引：7

作者：

Dahlhaus, R ^{[1
]}

机构：

[1] Univ Heidelberg, Inst Angew Math, D-69120 Heidelberg, Germany

来源：

ANNALS OF STATISTICS | 1997年 / 25卷 / 01期

关键词：

nonstationary processes; time series; evolutionary spectra; minimum distance estimates; model selection;

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：

A general minimum distance estimation procedure is presented for nonstationary time series models that have an evolutionary spectral representation. The asymptotic properties of the estimate are derived under the assumption of possible model misspecification. For autoregressive processes with time varying coefficients, the estimate is compared to the least squares estimate. Furthermore, the behavior of estimates is explained when a stationary model is fitted to a nonstationary process.

引用

页码：1 / 37

页数：37

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