Wavelet-Based Exact Maximum Likelihood Estimation of Arfima (p,d,q) Parameters

In this paper, we modify wavelets so that wavelet coefficients become statistically independent. Under standard regularity conditions, we determine the distribution of the wavelet coefficients. Using the moving average representation of the ARFIMA(p,d,q) process, we obtain wavelet-based exact maximum likelihood estimators of the ARFIMA(p,d,q) parameters. The corresponding Fisher information matrix is also derived

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Year of publication:	[2009]
Authors:	Gonzaga, Alex
Other Persons:	Bonzo, Daniel (contributor)
Publisher:	[2009]: [S.l.] : SSRN
Subject:	Maximum-Likelihood-Schätzung \| Maximum likelihood estimation \| Schätztheorie \| Estimation theory \| ARMA-Modell \| ARMA model
Description of contents:	Abstract [papers.ssrn.com]

Extent:	1 Online-Ressource
Type of publication:	Book / Working Paper
Language:	English
Notes:	In: The Philippine Statistician, Vol. 49, No. 1-4, pp. 57-71, 2000 Nach Informationen von SSRN wurde die ursprüngliche Fassung des Dokuments 2000 erstellt Volltext nicht verfügbar
Classification:	C13 - Estimation ; C22 - Time-Series Models
Source:	ECONIS - Online Catalogue of the ZBW

Persistent link: https://www.econbiz.de/10012764215