Optimal Variable Acceptance Sampling Plan under Progressive Type-II Censoring for Mixture Distribution: Applications in Breast Cancer Data

Optimal Variable Acceptance Sampling Plan under Progressive Type-II Censoring for Mixture Distribution: Applications in Breast Cancer Data | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Optimal Variable Acceptance Sampling Plan under Progressive Type-II Censoring for Mixture Distribution: Applications in Breast Cancer Data Ashlyn Maria Mathai, Mahesh Kumar This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3957711/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Mixture distributions are widely utilized in various practical problems such as clinical experiments and electronic component life testing. Despite this, the literature does not extensively cover acceptance sampling plans associated with these distributions. In this paper, variable acceptance sampling plans are designed for an exponential-Rayleigh mixture distribution using partially accelerated life tests (PALT). Under progressive type-II censoring schemes with binomial removals, the maximum likelihood estimates (MLEs) of the unknown parameters of the mixture distribution are derived for Arrhenius and linear life-stress relationships. Based on these relationships, optimal variable sampling plans are formulated and plan parameters are determined by solving corresponding optimization problems. The study presents numerical findings, a comparative analysis, and sensitivity assessments. Finally, the practical applicability and relevance of the proposed acceptance sampling plans are demonstrated using real-world datasets of breast cancer patients' records and failure lifetime data from communication transmitter-receivers in a commercial aircraft. Exponential Rayleigh mixture distribution Progressive type-II censoring Arrhenius life-stress relation partially accelerated life test optimal test plan Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-3957711","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":276169396,"identity":"06f99298-0b64-41fb-948a-d778e3774c9c","order_by":0,"name":"Ashlyn Maria Mathai","email":"","orcid":"","institution":"National Institute of Technology Calicut","correspondingAuthor":false,"prefix":"","firstName":"Ashlyn","middleName":"Maria","lastName":"Mathai","suffix":""},{"id":276169397,"identity":"7c61cdac-c92c-4969-bab5-cf294501a50c","order_by":1,"name":"Mahesh Kumar","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAu0lEQVRIiWNgGAWjYFACHgYGxgYbBjYElzgtaQxsbCRqOcwAt4Yg0G0/e/Dhzx3n8/jkmx8w/KhhkDEnpMXsTF6yMe+Z28VsbGwGjD3HGHgsGwhpOZBjJs3YdjuxjQ3oQt4GBh6DA4S0nH9j/vNn2zmwFsa/RGm5kWPGwNt2AKyFmThbbrwxluZtSwZqSTM4LHNMghiH5Rh+/Nlmlzi/+fDDh29qbOwJakEBQMUSpKgfBaNgFIyCUYALAAAEuDqpXMPDFAAAAABJRU5ErkJggg==","orcid":"","institution":"National Institute of Technology Calicut","correspondingAuthor":true,"prefix":"","firstName":"Mahesh","middleName":"","lastName":"Kumar","suffix":""}],"badges":[],"createdAt":"2024-02-15 05:48:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3957711/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3957711/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":52925219,"identity":"5013e6d5-1c8b-4356-9288-0b233ef5f0c4","added_by":"auto","created_at":"2024-03-18 18:01:14","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":506723,"visible":true,"origin":"","legend":"","description":"","filename":"MKAMMMCAP.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3957711/v1_covered_845acdba-f868-40ad-bcb9-adcc9090751e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Optimal Variable Acceptance Sampling Plan under Progressive Type-II Censoring for Mixture Distribution: Applications in Breast Cancer Data","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":" Exponential Rayleigh mixture distribution, Progressive type-II censoring, Arrhenius life-stress relation, partially accelerated life test, optimal test plan","lastPublishedDoi":"10.21203/rs.3.rs-3957711/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3957711/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Mixture distributions are widely utilized in various practical problems such as clinical experiments and electronic component life testing. 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