Diverging moments and parameter estimation

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dc.citation.bibtexNamearticleen_US
dc.citation.journalTitleJournal of the American Statistical Associationen_US
dc.contributor.authorGoncalves, Pauloen_US
dc.contributor.authorRiedi, Rudolf H.en_US
dc.contributor.orgCenter for Multimedia Communications (http://cmc.rice.edu/)en_US
dc.contributor.orgDigital Signal Processing (http://dsp.rice.edu/)en_US
dc.date.accessioned2007-10-31T00:44:52Zen_US
dc.date.available2007-10-31T00:44:52Zen_US
dc.date.issued2004-01-15en_US
dc.date.modified2004-09-03en_US
dc.date.submitted2002-12-05en_US
dc.descriptionJournal Paperen_US
dc.description.abstractHeavy tailed distributions enjoy increased popularity and become more readily applicable as the arsenal of analytical and numerical tools grows. They play key roles in modeling approaches in networking, finance, hydrology to name but a few. The tail parameter is of central importance as it governs both the existence of moments of positive order and the thickness of the tails of the distribution. Some of the best known tail estimators such as Koutrouvelis and Hill are either parametric or show lack in robustness or accuracy. This paper develops a shift and scale invariant, non-parametric estimator for both, upper and lower bounds for orders with finite moments. The estimator builds on the equivalence between tail behavior and the regularity of the characteristic function at the origin and achieves its goal by deriving a simplified wavelet analysis which is particularly suited to characteristic functions.en_US
dc.description.sponsorshipDefense Advanced Research Projects Agencyen_US
dc.description.sponsorshipNational Science Foundationen_US
dc.identifier.citationP. Goncalves and R. H. Riedi, "Diverging moments and parameter estimation," <i>Journal of the American Statistical Association,</i> 2004.en_US
dc.identifier.doihttp://dx.doi.org/10.1198/016214505000000303en_US
dc.identifier.urihttps://hdl.handle.net/1911/19903en_US
dc.language.isoengen_US
dc.subjectDiverging momentsen_US
dc.subjectheavy tail distributionsen_US
dc.subjectcharacteristic functionsen_US
dc.subjectwavelet transformen_US
dc.subjectmultifractal analysis.en_US
dc.subject.keywordDiverging momentsen_US
dc.subject.keywordheavy tail distributionsen_US
dc.subject.keywordcharacteristic functionsen_US
dc.subject.keywordwavelet transformen_US
dc.subject.keywordmultifractal analysis.en_US
dc.subject.otherWavelet based Signal/Image Processingen_US
dc.subject.otherMultiscale Methodsen_US
dc.subject.otherMultifractalsen_US
dc.subject.otherSignal Processing Applicationsen_US
dc.subject.otherTime Frequency and Spectral Analysisen_US
dc.titleDiverging moments and parameter estimationen_US
dc.typeJournal articleen_US
dc.type.dcmiTexten_US
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