Shrinkage Methods for Estimating the Shape Parameter of the Generalized Pareto Distribution

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dc.contributor.authorPels, Wilhemina Adoma
dc.contributor.authorAdebanji, Atinuke O.
dc.contributor.authorTwumasi-Ankrah, Sampson
dc.contributor.authorMinkah, Richard
dc.contributor.orcidhttps://orcid.org/0000-0001-7881-3069
dc.date.accessioned2023-12-06T10:02:56Z
dc.date.available2023-12-06T10:02:56Z
dc.date.issued2023
dc.descriptionAn article published in Journal of Applied Mathematics,Volume 2023, Article ID 9750638, 11 pages https://doi.org/10.1155/2023/9750638
dc.description.abstractThe generalized Pareto distribution is one of the most important distributions in statistics of extremes as it has wide applications in fields such as finance, insurance, and hydrology. This study proposes two new methods for estimating the shape parameter of the generalized Pareto distribution (GPD). The proposed methods use the shrinkage principle to adapt the existing empirical Bayesian with data-based prior and the likelihood moment method to obtain two estimators. The performance of the proposed estimators is compared with the existing estimators (i.e., maximum likelihood, likelihood moment estimators, etc.) for the shape parameter of the generalized Pareto distribution in a simulation study. The results show that the proposed estimators perform better for small to moderate number of exceedances in estimating shape parameter of the light-tailed distributions and competitive when estimating heavy-tailed distributions. The proposed estimators are illustrated with practical datasets from climate and insurance studies.
dc.description.sponsorshipKNUST
dc.identifier.citationJournal of Applied Mathematics Volume 2023, Article ID 9750638, 11 pages, https://doi.org/10.1155/2023/9750638
dc.identifier.urihttps://doi.org/10.1155/2023/9750638
dc.identifier.urihttps://ir.knust.edu.gh/handle/123456789/14636
dc.language.isoen
dc.publisherJournal of Applied Mathematics
dc.titleShrinkage Methods for Estimating the Shape Parameter of the Generalized Pareto Distribution
dc.typeArticle
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