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Bayesian inference of lower percentiles within strength modeling
Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2021.
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| Other Authors: | |
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2021
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| _version_ | 1867613695276744704 |
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| access_status_str | Open Access |
| author2 | Ferreira, Johan T. |
| author_browse | Ferreira, Johan T. |
| author_facet | Ferreira, Johan T. |
| collection | Thesis |
| dc_rights_str_mv | © 2019 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 (Advanced Data Analytics))--University of Pretoria, 2021. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/78407 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:40:13.972Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2021 |
| publishDateRange | 2021 |
| publishDateSort | 2021 |
| 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:2263/78407 Bayesian inference of lower percentiles within strength modeling Ferreira, Johan T. u13087747@tuks.co.za Bekker, Andriette, 1958- Van Zyl, Christine Elizabeth UCTD Mathematical statistics Mini Dissertation (MSc (Advanced Data Analytics))--University of Pretoria, 2021. The interest in the study and modeling of the strength within material science has continuously been of interest within engineering and the built environment, with the Weibull distribution frequently being the model of choice in this area. Oftentimes there is a high cost involved with obtaining enough samples to perform suitable inference, and a Bayesian approach has exhibited suitable inference based on smaller samples for parameter- and confidence interval estimation. This study considers alternative Weibull candidates from a general Weibull family for the data likelihood candidates, and noninformative prior choices for parameters of these considered members are derived for their corresponding parameters. In addition to this, some previously unconsidered priors are introduced for consideration with the standard Weibull model. An introductory simulation study is presented and the effect of the alternative prior choices for the standard two-parameter Weibull model is investigated. Real data analysis rounds off the contributions of this study. DSTNRF-SAMRC South African Statistical Association Statistics MSc (Advanced Data Analytics) Restricted 2021-02-10T15:33:52Z 2021-02-10T15:33:52Z 2021-05-05 2021 Mini Dissertation * A2021 http://hdl.handle.net/2263/78407 en © 2019 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 Mathematical statistics Bayesian inference of lower percentiles within strength modeling |
| title | Bayesian inference of lower percentiles within strength modeling |
| title_full | Bayesian inference of lower percentiles within strength modeling |
| title_fullStr | Bayesian inference of lower percentiles within strength modeling |
| title_full_unstemmed | Bayesian inference of lower percentiles within strength modeling |
| title_short | Bayesian inference of lower percentiles within strength modeling |
| title_sort | bayesian inference of lower percentiles within strength modeling |
| topic | UCTD Mathematical statistics |
| url | http://hdl.handle.net/2263/78407 |