Parametric estimation for ARFIMA models via spectral methods

Mauro Coli (), Lara Fontanella () and Mariagrazia Granturco ()
Additional contact information
Mauro Coli: University “G. D'Annunzio”
Lara Fontanella: University “G. D'Annunzio”
Mariagrazia Granturco: University “G. D'Annunzio”

Statistical Methods & Applications, 2005, vol. 14, issue 1, No 3, 27 pages

Abstract: Abstract Given a fractional integrated, autoregressive, moving average,ARFIMA (p, d, q) process, the simultaneous estimation of the short and long memory parameters can be achieved by maximum likelihood estimators. In this paper, following a two-step algorithm, the coefficients are estimated combining the maximum likelihood estimators with the general orthogonal decomposition of stochastic processes. In particular, the principal component analysis of stochastic processes is exploited to estimate the short memory parameters, which are plugged into the maximum likelihood function to obtain the fractional differencingd.

Keywords: ARFIMA processes; Karhunen Loève decomposition; Whittle MLE (search for similar items in EconPapers)
Date: 2005
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DOI: 10.1007/BF02511572

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