Asymptotic analysis of non-stationary functional series TAR estimators

Author

Poulimenos, A.G. ; Fassois, D.

Author_Institution

Univ. of Patras, Patras

fYear

2007

fDate

27-29 June 2007

Firstpage

1

Lastpage

6

Abstract

Functional Series Time-dependent AutoRegressive (FS-TAR) models constitute an important class of models for non-stationary signal modelling. However, the asymptotic properties of "general" (not necessarily periodically evolving) FS-TAR estimators are not, yet, well understood. In the present study, the problem of establishing an asymptotic analysis framework capable of accounting for "general" FS-TAR estimators is considered. The proposed framework is used for deriving the asymptotic properties of the "general" FS-TAR Weighted Least Squares (WLS) estimator, while the validity of the asymptotic analysis results is confirmed through Monte Carlo experiments.

Keywords

autoregressive processes; series (mathematics); signal processing; FS-TAR model; asymptotic analysis framework; functional series time-dependent autoregressive model; general FS-TAR weighted least squares estimator; nonstationary functional series TAR estimators; nonstationary signal modelling; Aerospace engineering; Automation; Laboratories; Least squares approximation; Mechanical systems; Monte Carlo methods; Signal resolution; Stochastic processes; Stochastic systems; Technological innovation;

fLanguage

English

Publisher

ieee

Conference_Titel

Control & Automation, 2007. MED '07. Mediterranean Conference on

Conference_Location

Athens

Print_ISBN

978-1-4244-1282-2

Electronic_ISBN

978-1-4244-1282-2

Type

conf

DOI

10.1109/MED.2007.4433845

Filename

4433845