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dc.contributor.author | Headrick, Todd C. | |
dc.contributor.author | Pant, Mohan | |
dc.date.accessioned | 2013-01-31T15:47:57Z | |
dc.date.available | 2013-01-31T15:47:57Z | |
dc.date.issued | 2012 | |
dc.identifier.citation | Published in ISRN Applied Mathematics 2012 | en_US |
dc.identifier.uri | http://hdl.handle.net/10106/11266 | |
dc.description.abstract | This paper introduces the Tukey family of symmetric h and asymmetric hh-distributions in the contexts of univariate L-moments and the L-correlation. Included is the development of a procedure for specifying nonnormal distributions with controlled degrees of L-skew, L-kurtosis, and L-correlations. The procedure can be applied in a variety of settings such as modeling events 9e.g., risk analysis, extreme events) and Monte Carlo or simulation studies. Further, it is demonstrated that estimates of L-skew, L-kurtosis, and L-correlation are substantially superior to conventional product-moment estimates of skew, kurtosis, and Pearson correlation in terms of both relative bias and efficiency when heavy-tailed distributions are of concern. | en_US |
dc.language.iso | en_US | en_US |
dc.publisher | Hindawi Publishing Corporation, | en_US |
dc.subject | Monte Carlo | en_US |
dc.subject | Moments | en_US |
dc.subject | Tukey | en_US |
dc.title | Characterizing Tukey h and h-h distributions through L-moments and the L-correlation | en_US |
dc.type | Article | en_US |
dc.publisher.department | Department of Curriculum & Instruction, The University of Texas at Arlington | |
dc.identifier.externalLinkDescription | The original publication is available at Article DOI | en_US |
dc.identifier.doi | http://dx.doi.org/10.5402/2012/980153 | |
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