The Annals of Statistics

Adaptive estimation in time-series models

Feike C. Drost, Chris A. J. Klaassen, and Bas J. M. Werker

Full-text: Open access

Abstract

In a framework particularly suited for many time-series models we obtain a LAN result under quite natural and economical conditions. This enables us to construct adaptive estimators for (part of) the Euclidean parameter in these semiparametric models. Special attention is directed to group models in time series with the important subclass of models with time varying location and scale. Our set-up is confronted with the existing literature and, as examples, we reconsider linear regression and ARMA, TAR and ARCH models.

Article information

Source
Ann. Statist., Volume 25, Number 2 (1997), 786-817.

Dates
First available in Project Euclid: 12 September 2002

Permanent link to this document
https://projecteuclid.org/euclid.aos/1031833674

Digital Object Identifier
doi:10.1214/aos/1031833674

Mathematical Reviews number (MathSciNet)
MR1439324

Zentralblatt MATH identifier
0941.62093

Subjects
Primary: 62G05: Estimation
Secondary: 62F12: Asymptotic properties of estimators 62M10: Time series, auto-correlation, regression, etc. [See also 91B84]

Keywords
LAN in time series adaptive estimation semiparametrics

Citation

Drost, Feike C.; Klaassen, Chris A. J.; Werker, Bas J. M. Adaptive estimation in time-series models. Ann. Statist. 25 (1997), no. 2, 786--817. doi:10.1214/aos/1031833674. https://projecteuclid.org/euclid.aos/1031833674


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