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Distributional properties of ratios of gamma random variables in the context of quality control

Mini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2016.

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Other Authors: Human, Schalk William
Format: Thesis
Language:English
Published: University of Pretoria 2023
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access_status_str Open Access
author2 Human, Schalk William
author_browse Human, Schalk William
author_facet Human, Schalk William
collection Thesis
dc_rights_str_mv © 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.
description Mini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2016.
format Thesis
id oai:repository.up.ac.za:2263/93807
institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:39:16.035Z
license_str Other — see source repository
provenance_str_mv Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository
publishDate 2023
publishDateRange 2023
publishDateSort 2023
publisher University of Pretoria
publisherStr University of Pretoria
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source_str UPSpace — University of Pretoria Institutional Repository
spelling oai:repository.up.ac.za:2263/93807 Distributional properties of ratios of gamma random variables in the context of quality control Human, Schalk William Bekker, Andriette, 1958- Mijburgh, Philip Albert UCTD Gamma Multivariate beta Shift in process variance Statistical Process Control Mini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2016. This study emanates from a practical problem in the statistical process control (SPC) environment where the quality of a process is monitored. Speci cally, where the variance of a process is being assessed to be the same for all samples. In the traditional SPC environment the parameters of the underlying manufacturing process are usually assumed to be known. If, however, they are not known, they need to be estimated. Estimating these parameters and using them in control charts has many associated problems, especially when the samples that are used to calculate the estimates contain few data points. This study proposes a new control chart that is used to detect a shift in the process's variance, but that does not directly rely on parameter estimates, and as such overcomes many of these problem. The development of this newly proposed control chart gives rise to a new beta type distribution. An overview of the problem statement as identi ed in the eld of SPC is given and the newly developed beta type distribution is proposed. Some statistical properties of this distribution are studied and the e ect of di erent parameter choices on the shape of the distribution are investigated, with the focus speci cally on the bivariate case. Through simulation, a comparison study is also performed, comparing the newly proposed model with a generalised version of the Q chart model, which was studied in depth by Adamski (2014). Statistics MSc (Mathematical Statistics) Unrestricted Faculty of Natural and Agricultural Sciences 2023-12-19T09:05:55Z 2023-12-19T09:05:55Z 2017 2016 Mini Dissertation * A2017 http://hdl.handle.net/2263/93807 en © 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. application/pdf University of Pretoria
spellingShingle UCTD
Gamma
Multivariate beta
Shift in process variance
Statistical Process Control
Distributional properties of ratios of gamma random variables in the context of quality control
title Distributional properties of ratios of gamma random variables in the context of quality control
title_full Distributional properties of ratios of gamma random variables in the context of quality control
title_fullStr Distributional properties of ratios of gamma random variables in the context of quality control
title_full_unstemmed Distributional properties of ratios of gamma random variables in the context of quality control
title_short Distributional properties of ratios of gamma random variables in the context of quality control
title_sort distributional properties of ratios of gamma random variables in the context of quality control
topic UCTD
Gamma
Multivariate beta
Shift in process variance
Statistical Process Control
url http://hdl.handle.net/2263/93807