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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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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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 |
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Generalised multivariate beta type II distribution Sequential quality monitoring procedure Density functions Statistics UCTD |
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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> |
work_keys_str_mv |
AT adamskikarien generalisedbetatypeiidistributionsemanatingfromasequentialprocess |
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1719316227994681344 |