Skew-normal distributions : advances in theory and applications

dc.contributor.advisorBekker, Andriette, 1958-
dc.contributor.coadvisorArashi, Mohammad
dc.contributor.coadvisorFerreira, Johan T.
dc.contributor.postgraduateRowland, Brett William
dc.date.accessioned2023-12-19T09:00:04Z
dc.date.available2023-12-19T09:00:04Z
dc.date.created2018
dc.date.issued2017-08
dc.descriptionMini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2017.en_US
dc.description.abstractThe normal distribution is popular in many statistical contexts. However, due to its symmetry and tail behavior it may not necessarily be the best choice to use in many real world applications. In order to alleviate the aforementioned issues, a symmetric generalised normal distribution that exhibits flexibility in its tail behavior is proposed as candidate to apply existing skewing methodology to. Methods to approximate the characteristics of this new distribution and a corresponding stochastic representation is derived. The skewed version of the generalised normal distribution, along with other distributions, is used in a distribution fitting context and to approximate particular binomial distributions as an application.en_US
dc.description.availabilityUnrestricteden_US
dc.description.degreeMSc (Mathematical Statistics)en_US
dc.description.departmentStatisticsen_US
dc.description.facultyFaculty of Natural and Agricultural Sciencesen_US
dc.description.sponsorshipNational Research Foundation (NRF)en_US
dc.identifier.citation*en_US
dc.identifier.otherA2018en_US
dc.identifier.urihttp://hdl.handle.net/2263/93803
dc.language.isoenen_US
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.subjectUCTDen_US
dc.subjectApproximating binomial distributionen_US
dc.subjectDistribution fittingen_US
dc.subjectSkew generalised normalen_US
dc.subjectStochastic representationen_US
dc.titleSkew-normal distributions : advances in theory and applicationsen_US
dc.typeMini Dissertationen_US

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