Maximum Likelihood Estimates of Symmetric Stable Distribution Parameters

Maximum Likelihood Estimates of Symmetric Stable Distribution Parameters

A method is developed to directly obtain maximum likelihood estimates of symmetric stable distribution parameters. This is a difficult estimation problem since the likelihood function is expressed as an integral. The estimation routine is tested on a Monte Carlo sample and produces reasonable estima...

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Veröffentlicht in:Communications in statistics. Simulation and computation 1990-01, Vol.19 (4), p.1459-1464
Hauptverfasser: Wade Brorsen, B., Yang, Seung Ryong
Format: Artikel
Sprache:eng
Schlagworte:
Exact sciences and technology
leptokurtosis
Mathematics
non-linear optimization
Nonparametric inference
numerical integration
Paretian distribution
Probability and statistics
Sciences and techniques of general use
Statistics
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Zusammenfassung:A method is developed to directly obtain maximum likelihood estimates of symmetric stable distribution parameters. This is a difficult estimation problem since the likelihood function is expressed as an integral. The estimation routine is tested on a Monte Carlo sample and produces reasonable estimates.
ISSN:0361-0918
1532-4141
DOI:10.1080/03610919008812928