dc.contributor.advisor |
Millard, Sollie M. |
|
dc.contributor.coadvisor |
Kanfer, F.H.J. (Frans) |
|
dc.contributor.postgraduate |
Du Randt, Ruan Jean |
|
dc.date.accessioned |
2023-02-10T13:30:23Z |
|
dc.date.available |
2023-02-10T13:30:23Z |
|
dc.date.created |
2023 |
|
dc.date.issued |
2022 |
|
dc.description |
Mini Dissertation (MSc (eScience))--University of Pretoria, 2022. |
en_US |
dc.description.abstract |
This mini-dissertation considers semi-parametric finite mixtures of partially linear models with Gaussian errors and focuses on the estimation procedure for such models. The semi-parametric structure allows for flexible modelling of the expected value of the response variable. These models are used in cases where the regression structure include both parametric and non-parametric covariate structures. We demonstrate the properties of the profile likelihood expectation maximisation algorithm (PL-EM) using a simulation study. The estimation algorithm is also demonstrated on real data. Overall, the estimation procedure is adequate in estimating the parameters of the mixtures of partially linear models from the results obtained in both the simulation study and the real-world application. |
en_US |
dc.description.availability |
Unrestricted |
en_US |
dc.description.degree |
MSc (eScience) |
en_US |
dc.description.department |
Statistics |
en_US |
dc.description.sponsorship |
DSI-NICIS National e-Science Postgraduate Teaching and Training Platform (NEPTTP) |
en_US |
dc.identifier.citation |
* |
en_US |
dc.identifier.other |
A2023 |
|
dc.identifier.uri |
https://repository.up.ac.za/handle/2263/89418 |
|
dc.language.iso |
en |
en_US |
dc.publisher |
University of Pretoria |
|
dc.rights |
© 2022 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. |
|
dc.subject |
EM algorithm |
en_US |
dc.subject |
Local kernel regression |
|
dc.subject |
Non-parametric |
|
dc.subject |
Profile likelihood |
|
dc.subject |
Semi-parametric |
|
dc.subject |
UCTD |
|
dc.title |
Semi-parametric mixtures of partially linear models |
en_US |
dc.type |
Mini Dissertation |
en_US |