A maximum likelihood estimation approach for spliced distributions obtained through quantile splicing

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dc.contributor.advisor Otieno Mac'Oduol, Brenda
dc.contributor.coadvisor Van Staden, Paul J.
dc.contributor.postgraduate Van der Sande, Jeanne-Louise
dc.date.accessioned 2023-02-13T13:45:50Z
dc.date.available 2023-02-13T13:45:50Z
dc.date.created 2023-04
dc.date.issued 2022-11-30
dc.description Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2022. en_US
dc.description.abstract This mini-dissertation proposes constructing a family of spliced distributions at a point different from the median, hence k=1/4 instead of k=1/2, using the method of quantile splicing proposed by Mac'Oduol et al. (2020). General results of these families of distributions are developed and the maximum likelihood approach is explored and investigated for estimation purposes. Moreover, a numerical application is presented in order to illustrate the implementation and application of the proposed method. en_US
dc.description.availability Unrestricted en_US
dc.description.degree MSc (Advanced Data Analytics) en_US
dc.description.department Statistics en_US
dc.identifier.citation * en_US
dc.identifier.other A2023
dc.identifier.uri https://repository.up.ac.za/handle/2263/89460
dc.language.iso en en_US
dc.publisher University of Pretoria
dc.rights © 2022 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.subject Two-piece distribution en_US
dc.subject Quantile splicing en_US
dc.subject l-moment en_US
dc.subject Maximum likelihood estimation en_US
dc.subject Quantile-based distributions en_US
dc.subject UCTD
dc.title A maximum likelihood estimation approach for spliced distributions obtained through quantile splicing en_US
dc.type Mini Dissertation en_US


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