Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring
In this article, a parametric bootstrap control monitoring scheme equivalently known as control chart, is proposed for process monitoring of percentiles of the generalized exponential distribution for type-I hybrid censored data assuming in-control parameters to be unknown. Similar schemes can be d...
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Instituto Nacional de Estatística | Statistics Portugal
2025-02-01
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| Series: | Revstat Statistical Journal |
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| Online Access: | https://revstat.ine.pt/index.php/REVSTAT/article/view/492 |
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| author | Shovan Chowdhury Amarjit Kundu Bidhan Modok |
| author_facet | Shovan Chowdhury Amarjit Kundu Bidhan Modok |
| author_sort | Shovan Chowdhury |
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In this article, a parametric bootstrap control monitoring scheme equivalently known as control chart, is proposed for process monitoring of percentiles of the generalized exponential distribution for type-I hybrid censored data assuming in-control parameters to be unknown. Similar schemes can be derived for type-I and type-II censored data as a special case of the proposed censoring scheme. Monte Carlo simulations are carried out for various combinations of percentiles, false-alarm rates and sample sizes to evaluate the in-control performance of the proposed scheme in terms of average run lengths. The out-of-control behavior and performance of the scheme is thoroughly investigated for several choices of shifts in the parameters of the distribution. Conventional Shewhart-type scheme is also proposed under the same set-up asymptotically and compared with bootstrap scheme using a skewed data set. The chart under hybrid censoring scheme is found to be more effective than the same under type-I and type-II censoring schemes in terms of magnitude and speed of detection of out-of-control signals. Finally, an application of the proposed scheme is shown from clinical practice.
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| format | Article |
| id | doaj-art-9d1bda4f9bd24c39a7d0f3c3a9156d09 |
| institution | Kabale University |
| issn | 1645-6726 2183-0371 |
| language | English |
| publishDate | 2025-02-01 |
| publisher | Instituto Nacional de Estatística | Statistics Portugal |
| record_format | Article |
| series | Revstat Statistical Journal |
| spelling | doaj-art-9d1bda4f9bd24c39a7d0f3c3a9156d092025-02-06T10:52:22ZengInstituto Nacional de Estatística | Statistics PortugalRevstat Statistical Journal1645-67262183-03712025-02-0123110.57805/revstat.v23i1.492Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid CensoringShovan Chowdhury0Amarjit Kundu1Bidhan Modok2Indian Institute of ManagementRaigunj UniversityRaiganj University In this article, a parametric bootstrap control monitoring scheme equivalently known as control chart, is proposed for process monitoring of percentiles of the generalized exponential distribution for type-I hybrid censored data assuming in-control parameters to be unknown. Similar schemes can be derived for type-I and type-II censored data as a special case of the proposed censoring scheme. Monte Carlo simulations are carried out for various combinations of percentiles, false-alarm rates and sample sizes to evaluate the in-control performance of the proposed scheme in terms of average run lengths. The out-of-control behavior and performance of the scheme is thoroughly investigated for several choices of shifts in the parameters of the distribution. Conventional Shewhart-type scheme is also proposed under the same set-up asymptotically and compared with bootstrap scheme using a skewed data set. The chart under hybrid censoring scheme is found to be more effective than the same under type-I and type-II censoring schemes in terms of magnitude and speed of detection of out-of-control signals. Finally, an application of the proposed scheme is shown from clinical practice. https://revstat.ine.pt/index.php/REVSTAT/article/view/492average run lengthcontrol chartfalse alarm rategeneralized exponential distributionhybrid censoringparametric bootstrap |
| spellingShingle | Shovan Chowdhury Amarjit Kundu Bidhan Modok Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring Revstat Statistical Journal average run length control chart false alarm rate generalized exponential distribution hybrid censoring parametric bootstrap |
| title | Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring |
| title_full | Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring |
| title_fullStr | Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring |
| title_full_unstemmed | Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring |
| title_short | Control Monitoring Schemes for Monitoring Percentiles of Generalized Exponential Distribution with Hybrid Censoring |
| title_sort | control monitoring schemes for monitoring percentiles of generalized exponential distribution with hybrid censoring |
| topic | average run length control chart false alarm rate generalized exponential distribution hybrid censoring parametric bootstrap |
| url | https://revstat.ine.pt/index.php/REVSTAT/article/view/492 |
| work_keys_str_mv | AT shovanchowdhury controlmonitoringschemesformonitoringpercentilesofgeneralizedexponentialdistributionwithhybridcensoring AT amarjitkundu controlmonitoringschemesformonitoringpercentilesofgeneralizedexponentialdistributionwithhybridcensoring AT bidhanmodok controlmonitoringschemesformonitoringpercentilesofgeneralizedexponentialdistributionwithhybridcensoring |