A Novel Rayleigh Inverted Weibull Model for Medical and Insurance Analysis

A Novel Rayleigh Inverted Weibull Model for Medical and Insurance Analysis | 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 Article A Novel Rayleigh Inverted Weibull Model for Medical and Insurance Analysis I. Elbatal, Ehab M. Almetwally, Meraou M. A, Eslam Hussam, Elkhateeb S Aly, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7417070/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 This paper presents a statistical approach to enhance the distributional flexibility of some old conventional models. The proposed approach is the new modified G family of distributions to introduce new models. Utilizing the newly modified G family technique, an updated form of the Rayleigh Inverted Weibull model, referred to as the new modified Rayleigh Inverted Weibull model, is generated. Specific mathematical characteristics are derived. The maximum likelihood estimators for the model parameters are derived. A Monte Carlo simulation study is conducted to assess the efficiency of these estimators. Some actuarial metrics are computed, including value at risk and tail value at risk. The use of a real dataset demonstrated the model’s utility. Finally, we concluded with some major results reported in the conclusion section. Physical sciences/Engineering Physical sciences/Mathematics and computing Rayleigh Inverted Weibull distribution New Modified G- family Hazard function Maximum likelihood estimation Moments 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-7417070","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":510409781,"identity":"7a62ac4b-19f4-4186-bb5c-57554ddbf804","order_by":0,"name":"I. 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