Open Access
Translator Disclaimer
February 1997 Fitting time series models to nonstationary processes
R. Dahlhaus
Ann. Statist. 25(1): 1-37 (February 1997). DOI: 10.1214/aos/1034276620

Abstract

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.

Citation

Download Citation

R. Dahlhaus. "Fitting time series models to nonstationary processes." Ann. Statist. 25 (1) 1 - 37, February 1997. https://doi.org/10.1214/aos/1034276620

Information

Published: February 1997
First available in Project Euclid: 10 October 2002

zbMATH: 0871.62080
MathSciNet: MR1429916
Digital Object Identifier: 10.1214/aos/1034276620

Subjects:
Primary: 62M15
Secondary: 62F10

Rights: Copyright © 1997 Institute of Mathematical Statistics

JOURNAL ARTICLE
37 PAGES


SHARE
Vol.25 • No. 1 • February 1997
Back to Top