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Maximum likelihood estimation when modelling in terms of constraints
Thesis (PhD)--University of Pretoria, 1995.
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University of Pretoria
2021
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| _version_ | 1867613622708994048 |
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| access_status_str | Open Access |
| author2 | Crowther, N.A.S. (Nicolaas Andries Sadie), 1944- |
| author_browse | Crowther, N.A.S. (Nicolaas Andries Sadie), 1944- |
| author_facet | Crowther, N.A.S. (Nicolaas Andries Sadie), 1944- |
| 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 | Thesis (PhD)--University of Pretoria, 1995. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/82481 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:39:04.809Z |
| 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:2263/82481 Maximum likelihood estimation when modelling in terms of constraints Crowther, N.A.S. (Nicolaas Andries Sadie), 1944- Matthews, Glenda Beverley UCTD modelling in terms of constraints Thesis (PhD)--University of Pretoria, 1995. A maximum likelihood (ML) estimation procedure is developed to find the mean of the exponential family subject to the constraints g(μ) = 0, where g is a vector valued function of the mean μ, satisfying the usual regularity constraints. This result forms the basis of an iterative procedure whereby the ML estimates of the mean values of a particular model are found. The constraints on the mean vector may be linear or non-linear. The application of the procedure provides a very :flexible method for modelling data either directly in terms of certain constraints or in terms of the implied constraints of the appropriate model. The approach accommodates any choice of model assuming any predetermined distribution of the error terms, provided that the covariance matrix of the error terms can be computed. Statistics PhD Unrestricted 2021-11-02T10:19:38Z 2021-11-02T10:19:38Z 2021 1995 Thesis * http://hdl.handle.net/2263/82481 © 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 modelling in terms of constraints Maximum likelihood estimation when modelling in terms of constraints |
| title | Maximum likelihood estimation when modelling in terms of constraints |
| title_full | Maximum likelihood estimation when modelling in terms of constraints |
| title_fullStr | Maximum likelihood estimation when modelling in terms of constraints |
| title_full_unstemmed | Maximum likelihood estimation when modelling in terms of constraints |
| title_short | Maximum likelihood estimation when modelling in terms of constraints |
| title_sort | maximum likelihood estimation when modelling in terms of constraints |
| topic | UCTD modelling in terms of constraints |
| url | http://hdl.handle.net/2263/82481 |