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The statistical modelling of growth

Thesis (PhD (Mathematical Statistics))--University of Pretoria, 1993.

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Other Authors: Du Toit, S.H.C.
Format: Thesis
Language:English
Published: University of Pretoria 2024
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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 Thesis (PhD (Mathematical Statistics))--University of Pretoria, 1993.
format Thesis
id oai:repository.up.ac.za:2263/99586
institution University of Pretoria (South Africa)
language English
last_indexed 2026-06-10T12:37:01.063Z
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:2263/99586 The statistical modelling of growth Du Toit, S.H.C. Herbst, Alida Statistical modelling Growth UCTD Thesis (PhD (Mathematical Statistics))--University of Pretoria, 1993. In many fields of application, such as biology, psychology, agriculture, geology, botany, engineering and medicine, experiments are conducted in which a number of responses are repeatedly measured on each of a number of experimental units under differing experimental conditions. Longitudinal data which consists of observations that are ordered by time or position in space, for example the height of a child measured annually or monthly over a period of time, is considered. The study of growth in height is an excellent model for the investigation of other forms of growth and is considered in the practical applications of this thesis. Any progress made in measuring and modelling physical growth will serve as a good basis when attempts are made in future on the more difficult task of describing cognitive, affective or social development. The Richards growth function, a generalisation of nonlinear functions with a flexible point of inflection, often used to describe and compare growth curves, is considered. The generalised least squares, the maximum likelihood and the asymptotic distribution free frequentist estimation procedures for linear and nonlinear random parameter models are discussed. Two algorithms namely the Fisher scoring algorithm and the Expected Maximization (EM) algorithm are discussed. The Gauss quadrature numerical integration technique, which usually provide reliable approximations when closed form solutions for integrals are not available, is considered. The Bayes and Maximum Aposteriori (MAP) estimators are discussed, for linear and nonlinear models. An empirical Bayes method for the estimation of unknown model parameters is applied to an incomparable collection of longitudinal human growth records begun at the Fels institute in 1929, as well as to the Berkeley human growth records ( see Tuddenham and Snyder, 1954). The nonlinear fixed and random parameter Richards models with time series deviations (ARMA(l,l)), for non-consecutive data, are considered and applied to different datasets. Most of the theory discussed has been implemented in computer programs Statistics PhD (Mathematical Statistics) 2024-11-27T09:16:21Z 2024-11-27T09:16:21Z 22/02/08 1993 Thesis http://hdl.handle.net/2263/99586 en © 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 Statistical modelling
Growth
UCTD
The statistical modelling of growth
title The statistical modelling of growth
title_full The statistical modelling of growth
title_fullStr The statistical modelling of growth
title_full_unstemmed The statistical modelling of growth
title_short The statistical modelling of growth
title_sort statistical modelling of growth
topic Statistical modelling
Growth
UCTD
url http://hdl.handle.net/2263/99586