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Mini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2016.
| Other Authors: | |
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2023
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| _version_ | 1867613634566291456 |
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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 |
| record_format | dspace |
| 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 |