Fitting time series models to nonstationary processes
成果类型:
Article
署名作者:
Dahlhaus, R
署名单位:
Ruprecht Karls University Heidelberg
刊物名称:
ANNALS OF STATISTICS
ISSN/ISSBN:
0090-5364
发表日期:
1997
页码:
1-37
关键词:
stationary-processes
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.