Please use this identifier to cite or link to this item: http://hdl.handle.net/10419/85212
Authors: 
Beran, Jan
Feng, Yuanhua
Year of Publication: 
2001
Series/Report no.: 
CoFE Discussion Paper 01/11
Abstract: 
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.
Subjects: 
semiparametric models
long-range dependence
fractional ARIMA
antipersistence
nonparametric regression
bandwidth selection
Persistent Identifier of the first edition: 
Document Type: 
Working Paper

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