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Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter
Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 1991.
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| Format: | Thesis |
| Language: | Afr |
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University of Pretoria
2024
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| _version_ | 1867613454775353344 |
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| access_status_str | Open Access |
| author2 | Du Toit, S.H.C. |
| author_browse | Du Toit, S.H.C. |
| author_facet | Du Toit, S.H.C. |
| collection | Thesis |
| dc_rights_str_mv | © 2024 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 | Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 1991. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/99578 |
| institution | University of Pretoria (South Africa) |
| language | Afr |
| last_indexed | 2026-06-10T12:36:24.683Z |
| 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:2263/99578 Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter Du Toit, S.H.C. Basson, Elizabeth M. Tydreekse Waarnemings Toestandruimte Kalmanfilter UCTD Dissertation (MSc (Mathematical Statistics))--University of Pretoria, 1991. The problem of estimating the parameters of an autoregressive moving average (ARMA) process based on a time series with missing observations, is considered. This paper describes a solution of the problem by using the state space approach. The method of calculating the exact likelihood function of a ARMA time series based on the state space representation and using Kalman recursive estimation, is modified to accommodate the missing values. This is accomplished via the prediction error decomposition of the likelihood function. Other possible methods for handling time series with missing data are discussed. Of these, four are chosen for numerical comparison of the results obtained by the state space approach. The main conclusion that is drawn is that several techniques, including the state space approach, appear to perform equally well for shorter stretches of missing data, and equally poor for longer stretches. Statistics MSc (Mathematical Statistics) 2024-11-27T09:16:19Z 2024-11-27T09:16:19Z 22/01/12 1991 Dissertation http://hdl.handle.net/2263/99578 Afr © 2024 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 | Tydreekse Waarnemings Toestandruimte Kalmanfilter UCTD Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter |
| title | Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter |
| title_full | Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter |
| title_fullStr | Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter |
| title_full_unstemmed | Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter |
| title_short | Hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die Kalmanfilter |
| title_sort | hantering van tydreekse met verlore waarnemings met behulp van die toestandruimte benadering en die kalmanfilter |
| topic | Tydreekse Waarnemings Toestandruimte Kalmanfilter UCTD |
| url | http://hdl.handle.net/2263/99578 |