Analyzing COVID-19 Trends in Canada, Mexico, and the Netherlands Using the Harris Extended Inverted Kumaraswamy Distribution

Analyzing COVID-19 Trends in Canada, Mexico, and the Netherlands Using the Harris Extended Inverted Kumaraswamy Distribution | 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 Analyzing COVID-19 Trends in Canada, Mexico, and the Netherlands Using the Harris Extended Inverted Kumaraswamy Distribution Jabir Bengalath, Bindu Punathumparambath This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4736148/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 30 Sep, 2024 Read the published version in International Journal of Data Science and Analytics → Version 1 posted 8 You are reading this latest preprint version Abstract Statistical probability distributions are frequently used in real-world data analysis. However, data from fields such as environmental science, finance, and biomedical sciences may not always fit in classical distributions. This usually requires the development of new distributions that better reflect data behavior in a variety of situations. In this paper, we introduce a new four-parameter distribution termed the Harris extended inverted Kumaraswamy(HEIK) distribution, is proposed and analyzed in detail. This generalization accommodates well-known submodels including MOEIK, IK, Lomax, MOL, Beta Type II, and others, as observed in this study. The study includes the basic properties of the observed probabilistic model. Explicit expressions for major mathematical properties of this distribution such as quantile function, complete moments, incomplete moments, conditional moments, and inverted moments. The entropy measure and order statistics are derived. The maximum likelihood estimation method is used to estimate the parameters. Simulation studies are conducted for different parameter values and compare the performance of the HEIK distribution. Real-life COVID-19 data from three countries are provided to demonstrate the potentiality and reliability of the extended distribution model have wider applications in many fields. Inverted Kumaraswamy distribution Harris Extended Inverted Kumaraswamy distribution Structural properties Parameter estimation Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 30 Sep, 2024 Read the published version in International Journal of Data Science and Analytics → Version 1 posted Editorial decision: Revision requested 21 Aug, 2024 Reviewers agreed at journal 03 Aug, 2024 Reviews received at journal 03 Aug, 2024 Reviewers agreed at journal 02 Aug, 2024 Reviewers invited by journal 02 Aug, 2024 Editor assigned by journal 28 Jul, 2024 Submission checks completed at journal 15 Jul, 2024 First submitted to journal 13 Jul, 2024 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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