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The estimation of missing values in hydrological records using the EM algorithm and regression methods
Includes bibliography.
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| Main Author: | |
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| Other Authors: | |
| Format: | Thesis |
| Language: | English |
| Published: |
Department of Statistical Sciences
2016
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| _version_ | 1867613464918228992 |
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| access_status_str | Open Access |
| author | Makhuvha, Tondani |
| author2 | Zucchini, Walter |
| author_browse | Makhuvha, Tondani Zucchini, Walter |
| author_facet | Zucchini, Walter Makhuvha, Tondani |
| author_sort | Makhuvha, Tondani |
| collection | Thesis |
| description | Includes bibliography. |
| format | Thesis |
| id | oai:open.uct.ac.za:11427/17120 |
| institution | University of Cape Town (South Africa) |
| language | eng |
| last_indexed | 2026-06-10T12:36:34.467Z |
| license_str | Not specified — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UCTD — University of Cape Town Open Access Repository |
| publishDate | 2016 |
| publishDateRange | 2016 |
| publishDateSort | 2016 |
| publisher | Department of Statistical Sciences |
| publisherStr | Department of Statistical Sciences |
| record_format | dspace |
| source_str | UCTD — University of Cape Town Open Access Repository |
| spelling | oai:open.uct.ac.za:11427/17120 The estimation of missing values in hydrological records using the EM algorithm and regression methods Makhuvha, Tondani Zucchini, Walter Sparks, Ross S Rain and rainfall - Statistical methods Algorithms Regression analysis Includes bibliography. The objective of this thesis is to review existing methods for estimating missing values in rainfall records and to propose a number of new procedures. Two classes of methods are considered. The first is based on the theory of variable selection in regression. Here the emphasis is on finding efficient methods to identify the set of control stations which are likely to yield the best regression estimates of the missing values in the target station. The second class of methods is based on the EM algorithm, proposed by Dempster, Laird and Rubin (1977). The emphasis here is to estimate the missing values directly without first making a detailed selection of control stations. All "relevant" stations are included. This method has not previously been applied in the context of estimating missing rainfall values. 2016-02-18T12:16:10Z 2016-02-18T12:16:10Z 1988 Master Thesis Masters MSc http://hdl.handle.net/11427/17120 eng application/pdf Department of Statistical Sciences Faculty of Science University of Cape Town |
| spellingShingle | Rain and rainfall - Statistical methods Algorithms Regression analysis Makhuvha, Tondani The estimation of missing values in hydrological records using the EM algorithm and regression methods |
| thesis_degree_str | Master's |
| title | The estimation of missing values in hydrological records using the EM algorithm and regression methods |
| title_full | The estimation of missing values in hydrological records using the EM algorithm and regression methods |
| title_fullStr | The estimation of missing values in hydrological records using the EM algorithm and regression methods |
| title_full_unstemmed | The estimation of missing values in hydrological records using the EM algorithm and regression methods |
| title_short | The estimation of missing values in hydrological records using the EM algorithm and regression methods |
| title_sort | estimation of missing values in hydrological records using the em algorithm and regression methods |
| topic | Rain and rainfall - Statistical methods Algorithms Regression analysis |
| url | http://hdl.handle.net/11427/17120 |
| work_keys_str_mv | AT makhuvhatondani theestimationofmissingvaluesinhydrologicalrecordsusingtheemalgorithmandregressionmethods AT makhuvhatondani estimationofmissingvaluesinhydrologicalrecordsusingtheemalgorithmandregressionmethods |