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Lower quantile estimation within an artificially censored framework
Mini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2020.
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| Format: | Thesis |
| Language: | English |
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University of Pretoria
2023
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| _version_ | 1867613568682164224 |
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| access_status_str | Open Access |
| author2 | Bekker, Andriette, 1958- |
| author_browse | Bekker, Andriette, 1958- |
| author_facet | Bekker, Andriette, 1958- |
| 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, 2020. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/93828 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:38:13.361Z |
| 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:2263/93828 Lower quantile estimation within an artificially censored framework Bekker, Andriette, 1958- jarodsmith706@gmail.com Ferreira, Johan T. Smith, Jarod UCTD Adjusted Kolmogorov-Smirnov threshold selection technique Artificial censoring Bootstrap Lower quantile Semi-parametric Mini Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 2020. Quantile estimation is a vital aspect of statistical analyses in a variety of fields. For example, lower quantile estimation is crucial to ensure the safety and reliability of wood-built structures. Various statistical tech-niques, which include parametric, non-parametric and mixture modelling are available for estimation of lower quantiles. An intuitive approach would be to consider models that ˝t the tail of the sample instead of the entire range. Quantiles of interest can be estimated by arti˝cially censoring observations beyond a chosen threshold. The choice of threshold is crucial to ensure e°cient and unbiased quantile estimates, and usually the 10th empirical percentile is chosen as the threshold. [16] proposes a bootstrap approach in order to ob-tain a better threshold for the censored Weibull MLE, however, this approach is computationally expensive. A new threshold selection technique is proposed that makes use of a standardised-weighted adjusted trun-cated Kolmogorov-Smirnov test (SWAKS-MLE). The SWAKS-MLE outperforms in the bootstrap threshold censored Weibull MLE method, in addition to being vastly less computationally intensive. Statistics MSc (Mathematical Statistics) Unrestricted Faculty of Natural and Agricultural Sciences 2023-12-19T14:11:26Z 2023-12-19T14:11:26Z 2020-04 2020 Mini Dissertation * A2020 http://hdl.handle.net/2263/93828 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 Adjusted Kolmogorov-Smirnov threshold selection technique Artificial censoring Bootstrap Lower quantile Semi-parametric Lower quantile estimation within an artificially censored framework |
| title | Lower quantile estimation within an artificially censored framework |
| title_full | Lower quantile estimation within an artificially censored framework |
| title_fullStr | Lower quantile estimation within an artificially censored framework |
| title_full_unstemmed | Lower quantile estimation within an artificially censored framework |
| title_short | Lower quantile estimation within an artificially censored framework |
| title_sort | lower quantile estimation within an artificially censored framework |
| topic | UCTD Adjusted Kolmogorov-Smirnov threshold selection technique Artificial censoring Bootstrap Lower quantile Semi-parametric |
| url | http://hdl.handle.net/2263/93828 |