Full Text Available
Note: Clicking the button above will open the full text document at the original institutional repository in a new window.
Breaking the norm : approaches for symmetric, positive, and skewed data
Thesis (PhD (Mathematical Statistics))--University of Pretoria, 2023.
Saved in:
| Other Authors: | |
|---|---|
| Format: | Thesis |
| Language: | English |
| Published: |
University of Pretoria
2024
|
| Subjects: | |
| Tags: |
No Tags, Be the first to tag this record!
|
| _version_ | 1867613486966636544 |
|---|---|
| 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 | © 2023 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 | Thesis (PhD (Mathematical Statistics))--University of Pretoria, 2023. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/94224 |
| institution | University of Pretoria (South Africa) |
| language | English |
| last_indexed | 2026-06-10T12:36:55.449Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2024 |
| publishDateRange | 2024 |
| publishDateSort | 2024 |
| 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:2263/94224 Breaking the norm : approaches for symmetric, positive, and skewed data Bekker, Andriette, 1958- matthias@dilectum.co.za Arashi, Mohammad Wagener, Matthias Copulas Derivative-kernel Flexible interpretable gamma Flexible interpretable normal Heavy-tailed Skew UCTD SDG-09: Industry, innovation and infrastructure Economic and management science theses SDG-09 Thesis (PhD (Mathematical Statistics))--University of Pretoria, 2023. This research contributes to the advancement of flexible and interpretable models within distribution theory, which is a fundamental aspect of numerous academic disciplines. This study investigates and presents the derivative-kernel approach for extending distributions. This method yields new distributions for symmetric, skew, and positive data, making it applicable for a wide range of modelling tasks. These newly derived distributions enhance the normal and gamma distributions by incorporating easily interpretable and identifiable parameters while retaining tractable mathematical properties. Furthermore, these models have a solid statistical foundation for simulation and prediction through stochastic representations. Additionally, these models demonstrate proficient flexibility and modelling performance when applied to real data. The introduced skew distribution presents a new skewing mechanism that combines the best features of current leading methods. Consequently, this leads to improved accuracy and flexibility when modelling skewed data patterns. In today's rapidly evolving data landscape, with increasingly intricate data structures, these advancements provide vital tools for effectively interpreting and analysing diverse data patterns encountered in economics, psychology, engineering, and biology. National Research Foundation of South Africa (Ref.: SRUG2204203965; RA171022270376, UID:119109; RA211204653274, Grant No. 151035) Centre of Excellence in Mathematical and Statistical Sciences at the University of the Witwatersrand. Iran National Science Foundation, grant No. 4015320. Statistics PhD (Mathematical Statistics) Unrestricted Faculty of Economic And Management Sciences SDG-09: Industry, innovation and infrastructure 2024-02-01T11:31:42Z 2024-02-01T11:31:42Z 2024-05-15 2023-11-06 Thesis * A2024 http://hdl.handle.net/2263/94224 10.25403/UPresearchdata.24998816 en © 2023 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 | Copulas Derivative-kernel Flexible interpretable gamma Flexible interpretable normal Heavy-tailed Skew UCTD SDG-09: Industry, innovation and infrastructure Economic and management science theses SDG-09 Breaking the norm : approaches for symmetric, positive, and skewed data |
| title | Breaking the norm : approaches for symmetric, positive, and skewed data |
| title_full | Breaking the norm : approaches for symmetric, positive, and skewed data |
| title_fullStr | Breaking the norm : approaches for symmetric, positive, and skewed data |
| title_full_unstemmed | Breaking the norm : approaches for symmetric, positive, and skewed data |
| title_short | Breaking the norm : approaches for symmetric, positive, and skewed data |
| title_sort | breaking the norm approaches for symmetric positive and skewed data |
| topic | Copulas Derivative-kernel Flexible interpretable gamma Flexible interpretable normal Heavy-tailed Skew UCTD SDG-09: Industry, innovation and infrastructure Economic and management science theses SDG-09 |
| url | http://hdl.handle.net/2263/94224 |