Zobrazit minimální záznam

dc.contributor.authorShafiq, Anum
dc.contributor.authorSindhu, Tabassum Naz
dc.contributor.authorRiaz, Muhammad Bilal
dc.contributor.authorHassan, Marwa K. H.
dc.contributor.authorAbushal, Tahani A.
dc.date.accessioned2025-03-14T08:43:39Z
dc.date.available2025-03-14T08:43:39Z
dc.date.issued2024
dc.identifier.citationHeliyon. 2024, vol. 10, issue 9, art. no. e30762.cs
dc.identifier.issn2405-8440
dc.identifier.urihttp://hdl.handle.net/10084/155810
dc.description.abstractIn survival and stochastic lifespan modeling, numerous families of distributions are sometimes considered unnatural, unjustifiable theoretically, and occasionally superfluous. Here, a novel parsimonious survival model is developed using the Bilal distribution (BD) and the KavyaManoharan (KM) parsimonious transformation family. In addition to other analytical properties, the forms of probability density function (PDF) and behavior of the distributions ' hazard rates are analyzed. The insights are theoretical as well as practical. Theoretically, we offer explicit equations for the single and product moments of order statistics from Kavya-Manoharan Bilal Distribution. Practically, maximum likelihood (ML) technique, which is based on simple random sampling (SRS) and ranked set sampling (RSS) sample schemes, is employed to estimate the parameters. Numerical simulations are used as the primary methodology to compare the various sampling techniques.cs
dc.language.isoencs
dc.publisherElseviercs
dc.relation.ispartofseriesHeliyoncs
dc.relation.urihttps://doi.org/10.1016/j.heliyon.2024.e30762cs
dc.rights© 2024 The Authors. Published by Elsevier Ltd.cs
dc.rights.urihttp://creativecommons.org/licenses/by-nc/4.0/cs
dc.subjectKM transformationcs
dc.subjectranked set samplingcs
dc.subjectsurvival functioncs
dc.subjectsimulationcs
dc.subjectstatistical modelcs
dc.titleA statistical framework for a new Kavya-Manoharan Bilal distribution using ranked set sampling and simple random samplingcs
dc.typearticlecs
dc.identifier.doi10.1016/j.heliyon.2024.e30762
dc.rights.accessopenAccesscs
dc.type.versionpublishedVersioncs
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume10cs
dc.description.issue9cs
dc.description.firstpageart. no. e30762cs
dc.identifier.wos001239842200001


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Zobrazit minimální záznam

© 2024 The Authors. Published by Elsevier Ltd.
Kromě případů, kde je uvedeno jinak, licence tohoto záznamu je © 2024 The Authors. Published by Elsevier Ltd.