Prediction of future failures in the log-logistic distribution based on hybrid censored data

<p>We consider the prediction of future observations from the log-logistic distribution. The data is assumed hybrid right censored with possible left censoring. Different point predictors were derived. Specifically, we obtained the best unbiased, the conditional median, and the maximum likelih...

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محفوظ في:
التفاصيل البيبلوغرافية
المؤلف الرئيسي: Wassim R. Abou Ghaida (14152050) (author)
مؤلفون آخرون: Ayman Baklizi (14158944) (author)
منشور في: 2022
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الوسوم: إضافة وسم
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author Wassim R. Abou Ghaida (14152050)
author2 Ayman Baklizi (14158944)
author2_role author
author_facet Wassim R. Abou Ghaida (14152050)
Ayman Baklizi (14158944)
author_role author
dc.creator.none.fl_str_mv Wassim R. Abou Ghaida (14152050)
Ayman Baklizi (14158944)
dc.date.none.fl_str_mv 2022-11-22T21:15:21Z
dc.identifier.none.fl_str_mv 10.1007/s13198-021-01510-3
dc.relation.none.fl_str_mv https://figshare.com/articles/journal_contribution/Prediction_of_future_failures_in_the_log-logistic_distribution_based_on_hybrid_censored_data/21597741
dc.rights.none.fl_str_mv CC BY 4.0
info:eu-repo/semantics/openAccess
dc.subject.none.fl_str_mv Strategy, management and organisational behaviour
Engineering practice and education
Strategy and Management
Safety, Risk, Reliability and Quality
dc.title.none.fl_str_mv Prediction of future failures in the log-logistic distribution based on hybrid censored data
dc.type.none.fl_str_mv Text
Journal contribution
info:eu-repo/semantics/publishedVersion
text
contribution to journal
description <p>We consider the prediction of future observations from the log-logistic distribution. The data is assumed hybrid right censored with possible left censoring. Different point predictors were derived. Specifically, we obtained the best unbiased, the conditional median, and the maximum likelihood predictors. Prediction intervals were derived using suitable pivotal quantities and intervals based on the highest density. We conducted a simulation study to compare the point and interval predictors. It is found that the point predictor BUP and the prediction interval HDI have the best overall performance. An illustrative example based on real data is given. </p><h2>Other Information</h2> <p> Published in: International Journal of System Assurance Engineering and Management<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s13198-021-01510-3" target="_blank">http://dx.doi.org/10.1007/s13198-021-01510-3</a></p>
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identifier_str_mv 10.1007/s13198-021-01510-3
network_acronym_str Manara2
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oai_identifier_str oai:figshare.com:article/21597741
publishDate 2022
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rights_invalid_str_mv CC BY 4.0
spelling Prediction of future failures in the log-logistic distribution based on hybrid censored dataWassim R. Abou Ghaida (14152050)Ayman Baklizi (14158944)Strategy, management and organisational behaviourEngineering practice and educationStrategy and ManagementSafety, Risk, Reliability and Quality<p>We consider the prediction of future observations from the log-logistic distribution. The data is assumed hybrid right censored with possible left censoring. Different point predictors were derived. Specifically, we obtained the best unbiased, the conditional median, and the maximum likelihood predictors. Prediction intervals were derived using suitable pivotal quantities and intervals based on the highest density. We conducted a simulation study to compare the point and interval predictors. It is found that the point predictor BUP and the prediction interval HDI have the best overall performance. An illustrative example based on real data is given. </p><h2>Other Information</h2> <p> Published in: International Journal of System Assurance Engineering and Management<br> License: <a href="https://creativecommons.org/licenses/by/4.0" target="_blank">https://creativecommons.org/licenses/by/4.0</a><br>See article on publisher's website: <a href="http://dx.doi.org/10.1007/s13198-021-01510-3" target="_blank">http://dx.doi.org/10.1007/s13198-021-01510-3</a></p>2022-11-22T21:15:21ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.1007/s13198-021-01510-3https://figshare.com/articles/journal_contribution/Prediction_of_future_failures_in_the_log-logistic_distribution_based_on_hybrid_censored_data/21597741CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/215977412022-11-22T21:15:21Z
spellingShingle Prediction of future failures in the log-logistic distribution based on hybrid censored data
Wassim R. Abou Ghaida (14152050)
Strategy, management and organisational behaviour
Engineering practice and education
Strategy and Management
Safety, Risk, Reliability and Quality
status_str publishedVersion
title Prediction of future failures in the log-logistic distribution based on hybrid censored data
title_full Prediction of future failures in the log-logistic distribution based on hybrid censored data
title_fullStr Prediction of future failures in the log-logistic distribution based on hybrid censored data
title_full_unstemmed Prediction of future failures in the log-logistic distribution based on hybrid censored data
title_short Prediction of future failures in the log-logistic distribution based on hybrid censored data
title_sort Prediction of future failures in the log-logistic distribution based on hybrid censored data
topic Strategy, management and organisational behaviour
Engineering practice and education
Strategy and Management
Safety, Risk, Reliability and Quality