A new method for estimating parameters of a skewed alpha-stable distribution

Shay Maymon, Jonathan Friedmann, Hagit Messer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Estimating the parameters of a skewed α-stable distribution calls for estimation of four unknown parameters of the probability density function (PDF): the location parameter, the scale parameter, the characteristic exponent and the skewness parameter. We present cumulative distribution function (CDF) based estimators for either the location parameter, the skewness parameter, or the characteristic exponent. The estimators are simple, consistent and their asymptotic performance is analyzed. Of a particular interest is the new estimator for the skewness parameter which is given in a closed form, as a function of the other parameters. As such, it can be used for reducing the search dimension when joint parameter estimation of a skewed stable distribution is called for.

Original languageEnglish
Title of host publicationDesign and Implementation of Signal Processing SystemNeural Networks for Signal Processing Signal Processing EducationOther Emerging Applications of Signal ProcessingSpecial Sessions
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages3822-3825
Number of pages4
ISBN (Electronic)0780362934
DOIs
StatePublished - 2000
Event25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000 - Istanbul, Turkey
Duration: 5 Jun 20009 Jun 2000

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume6
ISSN (Print)1520-6149

Conference

Conference25th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2000
Country/TerritoryTurkey
CityIstanbul
Period5/06/009/06/00

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