Arbeitspapier

Recent Developments in Non- and Semiparametric Regression with Fractional Time Series Errors

This paper summarizes recent developments in non- and semiparametric regres- sion with stationary fractional time series errors, where the error process may be short-range, long-range dependent or antipersistent. The trend function in this model is estimated nonparametrically, while the dependence structure of the error process is estimated by approximate maximum likelihood. Asymptotic properties of these estimators are described briefly. The focus is on describing the developments of bandwidth selection in this context based on the iterative plug-in idea (Gasser et al., 1991) and some detailed computational aspects. Applications in the framework of the SEMIFAR (semiparametric fractional autoregressive) model (Beran, 1999) illustrate the practical usefulness of the methods described here.

Language: Englisch

Bibliographic citation: Series: CoFE Discussion Paper ; No. 02/13

Classification: Wirtschaft

Subject: Nonparametric regression
FARIMA error processes
bandwidth selection
iterative plug-in
SEMIFAR model
Regression
Nichtparametrisches Verfahren
Zeitreihenanalyse
Theorie
Statistischer Fehler

Event: Geistige Schöpfung

(who): Beran, Jan
Feng, Yuanhua

Event: Veröffentlichung

(who): University of Konstanz, Center of Finance and Econometrics (CoFE)

(where): Konstanz

(when): 2002

Handle: http://hdl.handle.net/10419/85229

URN: urn:nbn:de:bsz:352-opus-8384

Last update: 10.03.2025, 11:45 AM CET

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Arbeitspapier

Associated

Beran, Jan
Feng, Yuanhua
University of Konstanz, Center of Finance and Econometrics (CoFE)

Time of origin

2002

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Recent Developments in Non- and Semiparametric Regression with Fractional Time Series Errors

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