Autor(en): | Beran, Jan Feng, Yuanhua Ocker, Dirk |
Titel: | SEMIFAR models |
Sprache (ISO): | en |
Zusammenfassung: | Recent results on so-called SEMIFAR models introduced by Beran (1997) are discussed. The nonparametric deterministic trend is estimated by a kernel method. The differencing- and fractional differencing parameters as well as the autoregressive coefficients are estimated by an approximate maximum likelihood approach. A data-driven algorithm for estimating the whole model is proposed based on the iterative plug-in idea for selecting bandwidth in nonparametric regression with long-memory. Prediction for SEMIFAR models is also discussed briefly. Two examples illustrate the potential usefulness of these models in practice. |
Schlagwörter: | bandwidth BIC difference stationarity differencing forecasting fractional ARIMA kernel estimation long-range dependence semiparametric models trend |
URI: | http://hdl.handle.net/2003/4919 http://dx.doi.org/10.17877/DE290R-6932 |
Erscheinungsdatum: | 1999 |
Provinienz: | Universitätsbibliothek Dortmund |
Enthalten in den Sammlungen: | Sonderforschungsbereich (SFB) 475 |
Dateien zu dieser Ressource:
Datei | Beschreibung | Größe | Format | |
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99_03.pdf | DNB | 232.36 kB | Adobe PDF | Öffnen/Anzeigen |
tr03-99.ps | 566.55 kB | Postscript | Öffnen/Anzeigen |
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