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

In this paper data-driven algorithms for fitting SEMIFAR models (Beran, 1999) are proposed. The algorithms combine the data-driven estimation of the nonparamet- ric 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:	2001-11
Authors:	Beran, Jan ; Yuanhua.Feng
Institutions:	Zentrum für Finanzen und Ökonometrie, Fachbereich Wirtschaftswissenschaften
Subject:	semiparametric models \| long-range dependence \| fractional ARIMA \| antipersistence \| nonparametric regression \| bandwidth selection

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Extent:	application/pdf
Series:	CoFE Discussion Paper.
Type of publication:	Book / Working Paper
Language:	English
Notes:	Number 01-11 14 pages
Source:	RePEc - Research Papers in Economics

Persistent link: https://www.econbiz.de/10005146733