SEMIFAR models

Jan Beran, Yuanhua Feng and Dirk Ocker

No 1999,03, Technical Reports from Technische Universität Dortmund, Sonderforschungsbereich 475: Komplexitätsreduktion in multivariaten Datenstrukturen

Abstract: 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.

Keywords: trend differencing; long-range dependence; difference stationarity; fractional ARIMA; BIC; kernel estimation; bandwidth; semiparametric models; forecasting (search for similar items in EconPapers)
Date: 1999
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Citations: View citations in EconPapers (17)

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Persistent link: https://EconPapers.repec.org/RePEc:zbw:sfb475:199903

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