Estimation of the stress-strength reliability for the inverse Weibull distribution under adaptive type-II progressive hybrid censoring
In this article, we compare the maximum likelihood estimate (MLE) and the maximum product of spacing estimate (MPSE) of a stress-strength reliability model, θ = P(Y < X), under adaptive progressive type-II progressive hybrid censoring, when X and Y are independent random variables taken from the...
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| Veröffentlicht in: | PloS one 2022-11, Vol.17 (11), p.e0277514-e0277514 |
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| description | In this article, we compare the maximum likelihood estimate (MLE) and the maximum product of spacing estimate (MPSE) of a stress-strength reliability model, θ = P(Y < X), under adaptive progressive type-II progressive hybrid censoring, when X and Y are independent random variables taken from the inverse Weibull distribution (IWD) with the same shape parameter and different scale parameters. The performance of both estimators is compared, through a comprehensive computer simulation based on two criteria, namely bias and mean squared error (MSE). To demonstrate the effectiveness of our proposed methods, we used two examples of real-life data based on Breakdown Times of an Insulated Fluid by (Nelson, 2003) and Head and Neck Cancer Data by (Efron, 1988). It is concluded that the MPSE method outperformed the MLE method in terms of bias and MSE values. |
| doi_str_mv | 10.1371/journal.pone.0277514 |
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The performance of both estimators is compared, through a comprehensive computer simulation based on two criteria, namely bias and mean squared error (MSE). To demonstrate the effectiveness of our proposed methods, we used two examples of real-life data based on Breakdown Times of an Insulated Fluid by (Nelson, 2003) and Head and Neck Cancer Data by (Efron, 1988). It is concluded that the MPSE method outperformed the MLE method in terms of bias and MSE values.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0277514</identifier><identifier>PMID: 36378634</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Analysis ; Approximation ; Bias ; Censorship ; Computer Simulation ; Evaluation ; Experiments ; Failure ; Head & neck cancer ; Head and neck cancer ; Independent variables ; Likelihood Functions ; Maximum likelihood estimates ; Medicine and Health Sciences ; Parameters ; Physical Sciences ; Radiation therapy ; Random variables ; Reliability ; Reliability analysis ; Reproducibility of Results ; Research and Analysis Methods ; Simulation methods ; Statistical Distributions ; Weibull distribution</subject><ispartof>PloS one, 2022-11, Vol.17 (11), p.e0277514-e0277514</ispartof><rights>Copyright: © 2022 Alslman, Helu. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.</rights><rights>COPYRIGHT 2022 Public Library of Science</rights><rights>2022 Alslman, Helu. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2022 Alslman, Helu 2022 Alslman, Helu</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-585b87490bf9ad5358e564b65cd24c5c36175c2882075ede5e9115fe6cbcd1663</citedby><cites>FETCH-LOGICAL-c692t-585b87490bf9ad5358e564b65cd24c5c36175c2882075ede5e9115fe6cbcd1663</cites><orcidid>0000-0002-1958-8161</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9665393/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC9665393/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23845,27901,27902,53766,53768,79343,79344</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/36378634$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Yu, Lili</contributor><creatorcontrib>Alslman, Majd</creatorcontrib><creatorcontrib>Helu, Amal</creatorcontrib><title>Estimation of the stress-strength reliability for the inverse Weibull distribution under adaptive type-II progressive hybrid censoring</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>In this article, we compare the maximum likelihood estimate (MLE) and the maximum product of spacing estimate (MPSE) of a stress-strength reliability model, θ = P(Y < X), under adaptive progressive type-II progressive hybrid censoring, when X and Y are independent random variables taken from the inverse Weibull distribution (IWD) with the same shape parameter and different scale parameters. The performance of both estimators is compared, through a comprehensive computer simulation based on two criteria, namely bias and mean squared error (MSE). To demonstrate the effectiveness of our proposed methods, we used two examples of real-life data based on Breakdown Times of an Insulated Fluid by (Nelson, 2003) and Head and Neck Cancer Data by (Efron, 1988). It is concluded that the MPSE method outperformed the MLE method in terms of bias and MSE values.</description><subject>Analysis</subject><subject>Approximation</subject><subject>Bias</subject><subject>Censorship</subject><subject>Computer Simulation</subject><subject>Evaluation</subject><subject>Experiments</subject><subject>Failure</subject><subject>Head & neck cancer</subject><subject>Head and neck cancer</subject><subject>Independent variables</subject><subject>Likelihood Functions</subject><subject>Maximum likelihood estimates</subject><subject>Medicine and Health Sciences</subject><subject>Parameters</subject><subject>Physical Sciences</subject><subject>Radiation therapy</subject><subject>Random variables</subject><subject>Reliability</subject><subject>Reliability analysis</subject><subject>Reproducibility of Results</subject><subject>Research and Analysis Methods</subject><subject>Simulation methods</subject><subject>Statistical Distributions</subject><subject>Weibull 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Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PloS one</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Alslman, Majd</au><au>Helu, Amal</au><au>Yu, Lili</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Estimation of the stress-strength reliability for the inverse Weibull distribution under adaptive type-II progressive hybrid censoring</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2022-11-15</date><risdate>2022</risdate><volume>17</volume><issue>11</issue><spage>e0277514</spage><epage>e0277514</epage><pages>e0277514-e0277514</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>In this article, we compare the maximum likelihood estimate (MLE) and the maximum product of spacing estimate (MPSE) of a stress-strength reliability model, θ = P(Y < X), under adaptive progressive type-II progressive hybrid censoring, when X and Y are independent random variables taken from the inverse Weibull distribution (IWD) with the same shape parameter and different scale parameters. The performance of both estimators is compared, through a comprehensive computer simulation based on two criteria, namely bias and mean squared error (MSE). To demonstrate the effectiveness of our proposed methods, we used two examples of real-life data based on Breakdown Times of an Insulated Fluid by (Nelson, 2003) and Head and Neck Cancer Data by (Efron, 1988). It is concluded that the MPSE method outperformed the MLE method in terms of bias and MSE values.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>36378634</pmid><doi>10.1371/journal.pone.0277514</doi><tpages>e0277514</tpages><orcidid>https://orcid.org/0000-0002-1958-8161</orcidid><oa>free_for_read</oa></addata></record> |
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| subjects | Analysis Approximation Bias Censorship Computer Simulation Evaluation Experiments Failure Head & neck cancer Head and neck cancer Independent variables Likelihood Functions Maximum likelihood estimates Medicine and Health Sciences Parameters Physical Sciences Radiation therapy Random variables Reliability Reliability analysis Reproducibility of Results Research and Analysis Methods Simulation methods Statistical Distributions Weibull distribution |
| title | Estimation of the stress-strength reliability for the inverse Weibull distribution under adaptive type-II progressive hybrid censoring |
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