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On the reliability of Type II censored reliability analyses. / See Ju Chua

Swansea University Author: See Ju Chua

Abstract

This thesis considers the analysis of reliability data subject to censoring, and, in particular, the extent to which an interim analysis - here, using information based on Type II censoring - provides a guide to the final analysis. Under a Type II censored sampling, a random sample of n units is put...

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Published: 2009
Institution: Swansea University
Degree level: Doctoral
Degree name: Ph.D
URI: https://cronfa.swan.ac.uk/Record/cronfa42621
first_indexed 2018-08-02T18:55:09Z
last_indexed 2018-08-03T10:10:38Z
id cronfa42621
recordtype RisThesis
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spelling 2018-08-02T16:24:29.8682073 v2 42621 2018-08-02 On the reliability of Type II censored reliability analyses. 3bc86f473d65219199042e8fc95fd1c3 NULL See Ju Chua See Ju Chua true true 2018-08-02 This thesis considers the analysis of reliability data subject to censoring, and, in particular, the extent to which an interim analysis - here, using information based on Type II censoring - provides a guide to the final analysis. Under a Type II censored sampling, a random sample of n units is put on test simultaneously, and the test is terminated as soon as r (1 &le; r &le; n, although we are usually interested in r < n) failures are observed. In the case where all test units were observed to fail (r = n), the sample is complete. From a statistical perspective, the analysis of the complete sample is to be preferred, but, in practice, censoring is often necessary; such sampling plan can save money and time, since it could take a very long time for all units to fail in some instances. From a practical perspective, an experimenter may be interested to know the smallest number of failures at which the experiment can be reasonably or safely terminated with the interim analysis still providing a close and reliable guide to the analysis of the final, complete data. In this thesis, we aim to gain more insight into the roles of censoring number r and sample size n under this sampling plan. Our approach requires a method to measure the precision of a Type II censored estimate, calculated at censoring level r, in estimating the complete estimate, and hence the study of the relationship between interim and final estimates. For simplicity, we assume that the lifetimes follow the exponential distribution, and then adopt the methods to the two- parameter Weibull and Burr Type XII distributions, both are widely used in reliability modelling. We start by presenting some mathematical and computational methodology for estimating model parameters and percentile functions, by the method of maximum likelihood. Expressions for the asymptotic variances and covariances of the estimators are given. In practice, some indication of the likely accuracy of these estimates is often desired; the theory of asymptotic Normality of maximum likelihood estimator is convenient, however, we consider the use of relative likelihood contour plots to obtain approximate confidence regions of parameters in relatively small samples. Finally, we provide formulae of the correlations between the interim and final maximum likelihood estimators of model parameters and a particular percentile function, and discuss some practical implications of our work, based on the results obtained from published data and simulation experiments. E-Thesis Statistics. 31 12 2009 2009-12-31 COLLEGE NANME Economics COLLEGE CODE Swansea University Doctoral Ph.D 2018-08-02T16:24:29.8682073 2018-08-02T16:24:29.8682073 Faculty of Humanities and Social Sciences School of Management - Economics See Ju Chua NULL 1 0042621-02082018162508.pdf 10805379.pdf 2018-08-02T16:25:08.8830000 Output 11479573 application/pdf E-Thesis true 2018-08-02T16:25:08.8830000 false
title On the reliability of Type II censored reliability analyses.
spellingShingle On the reliability of Type II censored reliability analyses.
See Ju Chua
title_short On the reliability of Type II censored reliability analyses.
title_full On the reliability of Type II censored reliability analyses.
title_fullStr On the reliability of Type II censored reliability analyses.
title_full_unstemmed On the reliability of Type II censored reliability analyses.
title_sort On the reliability of Type II censored reliability analyses.
author_id_str_mv 3bc86f473d65219199042e8fc95fd1c3
author_id_fullname_str_mv 3bc86f473d65219199042e8fc95fd1c3_***_See Ju Chua
author See Ju Chua
author2 See Ju Chua
format E-Thesis
publishDate 2009
institution Swansea University
college_str Faculty of Humanities and Social Sciences
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hierarchy_top_id facultyofhumanitiesandsocialsciences
hierarchy_top_title Faculty of Humanities and Social Sciences
hierarchy_parent_id facultyofhumanitiesandsocialsciences
hierarchy_parent_title Faculty of Humanities and Social Sciences
department_str School of Management - Economics{{{_:::_}}}Faculty of Humanities and Social Sciences{{{_:::_}}}School of Management - Economics
document_store_str 1
active_str 0
description This thesis considers the analysis of reliability data subject to censoring, and, in particular, the extent to which an interim analysis - here, using information based on Type II censoring - provides a guide to the final analysis. Under a Type II censored sampling, a random sample of n units is put on test simultaneously, and the test is terminated as soon as r (1 &le; r &le; n, although we are usually interested in r < n) failures are observed. In the case where all test units were observed to fail (r = n), the sample is complete. From a statistical perspective, the analysis of the complete sample is to be preferred, but, in practice, censoring is often necessary; such sampling plan can save money and time, since it could take a very long time for all units to fail in some instances. From a practical perspective, an experimenter may be interested to know the smallest number of failures at which the experiment can be reasonably or safely terminated with the interim analysis still providing a close and reliable guide to the analysis of the final, complete data. In this thesis, we aim to gain more insight into the roles of censoring number r and sample size n under this sampling plan. Our approach requires a method to measure the precision of a Type II censored estimate, calculated at censoring level r, in estimating the complete estimate, and hence the study of the relationship between interim and final estimates. For simplicity, we assume that the lifetimes follow the exponential distribution, and then adopt the methods to the two- parameter Weibull and Burr Type XII distributions, both are widely used in reliability modelling. We start by presenting some mathematical and computational methodology for estimating model parameters and percentile functions, by the method of maximum likelihood. Expressions for the asymptotic variances and covariances of the estimators are given. In practice, some indication of the likely accuracy of these estimates is often desired; the theory of asymptotic Normality of maximum likelihood estimator is convenient, however, we consider the use of relative likelihood contour plots to obtain approximate confidence regions of parameters in relatively small samples. Finally, we provide formulae of the correlations between the interim and final maximum likelihood estimators of model parameters and a particular percentile function, and discuss some practical implications of our work, based on the results obtained from published data and simulation experiments.
published_date 2009-12-31T13:35:41Z
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score 11.247077

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