Quantile-based generalized logistic distribution

dc.contributor.advisorVan Staden, Paul J.
dc.contributor.emailpaul.vanstaden@up.ac.zaen_ZA
dc.contributor.postgraduateOmachar, Brenda V.
dc.date.accessioned2022-02-09T06:51:37Z
dc.date.available2022-02-09T06:51:37Z
dc.date.created2014
dc.date.issued2014
dc.descriptionDissertation (MSc)--University of Pretoria, 2014.en_ZA
dc.description.abstractThis dissertation proposes the development of a new quantile-based generalized logistic distribution GLDQB, by using the quantile function of the generalized logistic distribution (GLO) as the basic building block. This four-parameter distribution is highly flexible with respect to distributional shape in that it explains extensive levels of skewness and kurtosis through the inclusion of two shape parameters. The parameter space as well as the distributional shape properties are discussed at length. The distribution is characterized through its -moments and an estimation algorithm is presented for estimating the distribution’s parameters with method of -moments estimation. This new distribution is then used to fit and approximate the probability of a data set.en_ZA
dc.description.availabilityUnrestricteden_ZA
dc.description.degreeMScen_ZA
dc.description.departmentStatisticsen_ZA
dc.identifier.citation*en_ZA
dc.identifier.urihttp://hdl.handle.net/2263/83687
dc.language.isoenen_ZA
dc.publisherUniversity of Pretoria
dc.rights© 2021 University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria.
dc.subjectGeneralized logistic distributionen_ZA
dc.subjectL-Momentsen_ZA
dc.subjectQuantile functionen_ZA
dc.subjectUCTDen_ZA
dc.titleQuantile-based generalized logistic distributionen_ZA
dc.typeDissertationen_ZA

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