The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient

dc.contributor.authorCaeiro, Frederico
dc.contributor.authorHenriques-Rodrigues, Lígia
dc.contributor.authorGomes, M. Ivette
dc.date.accessioned2022-12-28T15:54:44Z
dc.date.available2022-12-28T15:54:44Z
dc.date.issued2022-06-26
dc.description.abstractDue to the specificity of the Weibull tail coefficient, most of the estimators available in the literature are based on the log excesses and are consequently quite similar to the estimators used for the estimation of a positive extreme value index. The interesting performance of estimators based on generalized means leads us to base the estimation of the Weibull tail coefficient on the power mean-of-order-. Consistency and asymptotic normality of the estimators under study are put forward. Their performance for finite samples is illustrated through a Monte Carlo simulation. It is always possible to find a negative value of (contrarily to what happens with the mean-of-order- estimator for the extreme value index), such that, for adequate values of the threshold, there is a reduction in both bias and root mean square error.por
dc.identifier.authoremailfac@fct.unl.pt
dc.identifier.authoremailligiahr@uevora.pt
dc.identifier.authoremailivette.gomes@fc.ul.pt
dc.identifier.citationFrederico Caeiro, Lígia Henriques-Rodrigues, M. Ivette Gomes, "The Use of Generalized Means in the Estimation of the Weibull Tail Coefficient", Computational and Mathematical Methods, vol. 2022, Article ID 7290822, 12 pages, 2022. https://doi.org/10.1155/2022/7290822por
dc.identifier.doihttps://doi.org/10.1155/2022/7290822por
dc.identifier.revistaComputational and Mathematical Methods
dc.identifier.scientificarea336por
dc.identifier.urihttps://www.hindawi.com/journals/cmm/2022/7290822/
dc.identifier.urihttp://hdl.handle.net/10174/32938
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherHindawipor
dc.rightsopenAccesspor
dc.titleThe Use of Generalized Means in the Estimation of the Weibull Tail Coefficientpor
dc.typearticlepor

Files

Original bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
7290822.pdf
Size:
1.05 MB
Format:
Adobe Portable Document Format

License bundle

Now showing 1 - 1 of 1
Loading...
Thumbnail Image
Name:
license.txt
Size:
3.89 KB
Format:
Item-specific license agreed upon to submission
Description: