Iterative plug-in algorithms for SEMIFAR models : definition, convergence and asymptotic properties

Jan Beran and Yuanhua Feng

In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparametric trend and maximum likelihood estimation of the parameters. Convergence and asymptotic properties of the proposed algorithms are investigated. A large simulation study illustrates the practical performance of the methods.

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Year of publication:	[2001]
Authors:	Beran, Jan ; Feng, Yuanhua
Publisher:	[Konstanz] : [Zentrum für Finanzen und Ökonometrie, Universität Konstanz]
Subject:	semiparametric models \| long-range dependence \| fractional ARIMA \| antipersistence \| nonparametric regression \| bandwidth selection \| Nichtparametrisches Verfahren \| Nonparametric statistics \| Modellierung \| Scientific modelling \| Theorie \| Theory \| ARMA-Modell \| ARMA model