Generalised beta type II distributions - emanating from a sequential process

This study focuses on the development of a generalised multivariate beta type II distribution as well as the noncentral and bimatrix counterparts with positive domain. These models emanate from a sequential quality monitoring procedure with the normal and multivariate normal distributions as the...

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Main Author: Adamski, Karien
Other Authors: Bekker, Andriette, 1958-
Language:en
Published: University of Pretoria 2014
Subjects:
Online Access:http://hdl.handle.net/2263/40233
Adamski, K 2013, Generalised beta type II distributions - emanating from a sequential process, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/40233>
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spelling ndltd-netd.ac.za-oai-union.ndltd.org-up-oai-repository.up.ac.za-2263-402332020-06-02T03:18:19Z Generalised beta type II distributions - emanating from a sequential process Adamski, Karien Bekker, Andriette, 1958- Human, Schalk William Roux, Jacobus J.J. Generalised multivariate beta type II distribution Sequential quality monitoring procedure Density functions Statistics UCTD This study focuses on the development of a generalised multivariate beta type II distribution as well as the noncentral and bimatrix counterparts with positive domain. These models emanate from a sequential quality monitoring procedure with the normal and multivariate normal distributions as the underlying process distributions. Three different scenarios are considered, namely: 1. The variance is monitored from a normal process and the mean remains unchanged; 2. The above-mentioned scenario but the known mean also encounters a sustained shift; 3. The covariance structure of a multivariate normal distribution is monitored with the known mean vector unchanged. The statistics originating from the above-mentioned scenarios considered are constructed from different dependent chi-squared or Wishart ratios. Exact expressions are derived for the probability density functions of these statistics. These new distributions contribute to the statistical discipline in the sense that it can serve as alternatives to existing probability models, and can be used in determining the performance of the quality monitoring procedure. Thesis (PhD)--University of Pretoria, 2013. gm2014 Statistics unrestricted 2014-06-17T13:04:15Z 2014-06-17T13:04:15Z 2014-04-23 2013 Thesis http://hdl.handle.net/2263/40233 Adamski, K 2013, Generalised beta type II distributions - emanating from a sequential process, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/40233> D14/4/124/gm en © 2013 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. University of Pretoria
collection NDLTD
language en
sources NDLTD
topic Generalised multivariate beta type II distribution
Sequential quality monitoring procedure
Density functions
Statistics
UCTD
spellingShingle Generalised multivariate beta type II distribution
Sequential quality monitoring procedure
Density functions
Statistics
UCTD
Adamski, Karien
Generalised beta type II distributions - emanating from a sequential process
description This study focuses on the development of a generalised multivariate beta type II distribution as well as the noncentral and bimatrix counterparts with positive domain. These models emanate from a sequential quality monitoring procedure with the normal and multivariate normal distributions as the underlying process distributions. Three different scenarios are considered, namely: 1. The variance is monitored from a normal process and the mean remains unchanged; 2. The above-mentioned scenario but the known mean also encounters a sustained shift; 3. The covariance structure of a multivariate normal distribution is monitored with the known mean vector unchanged. The statistics originating from the above-mentioned scenarios considered are constructed from different dependent chi-squared or Wishart ratios. Exact expressions are derived for the probability density functions of these statistics. These new distributions contribute to the statistical discipline in the sense that it can serve as alternatives to existing probability models, and can be used in determining the performance of the quality monitoring procedure. === Thesis (PhD)--University of Pretoria, 2013. === gm2014 === Statistics === unrestricted
author2 Bekker, Andriette, 1958-
author_facet Bekker, Andriette, 1958-
Adamski, Karien
author Adamski, Karien
author_sort Adamski, Karien
title Generalised beta type II distributions - emanating from a sequential process
title_short Generalised beta type II distributions - emanating from a sequential process
title_full Generalised beta type II distributions - emanating from a sequential process
title_fullStr Generalised beta type II distributions - emanating from a sequential process
title_full_unstemmed Generalised beta type II distributions - emanating from a sequential process
title_sort generalised beta type ii distributions - emanating from a sequential process
publisher University of Pretoria
publishDate 2014
url http://hdl.handle.net/2263/40233
Adamski, K 2013, Generalised beta type II distributions - emanating from a sequential process, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd <http://hdl.handle.net/2263/40233>
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