{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,15]],"date-time":"2025-12-15T19:54:10Z","timestamp":1765828450289,"version":"build-2065373602"},"reference-count":41,"publisher":"MDPI AG","issue":"12","license":[{"start":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T00:00:00Z","timestamp":1732233600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Entropy"],"abstract":"<jats:p>This paper presents a new methodology for generating continuous statistical distributions, integrating the exponentiated odds ratio within the framework of survival analysis. This new method enhances the flexibility and adaptability of distribution models to effectively address the complexities inherent in contemporary datasets. The core of this advancement is illustrated by introducing a particular subfamily, the \u201cType 2 Gumbel Weibull-G family of distributions\u201d. We provide a comprehensive analysis of the mathematical properties of these distributions, including statistical properties such as density functions, moments, hazard rate and quantile functions, R\u00e9nyi entropy, order statistics, and the concept of stochastic ordering. To test the robustness of our new model, we apply five distinct methods for parameter estimation. The practical applicability of the Type 2 Gumbel Weibull-G distributions is further supported through the analysis of three real-world datasets. These real-life applications illustrate the exceptional statistical precision of our distributions compared to existing models, thereby reinforcing their significant value in both theoretical and practical statistical applications.<\/jats:p>","DOI":"10.3390\/e26121006","type":"journal-article","created":{"date-parts":[[2024,11,22]],"date-time":"2024-11-22T06:41:48Z","timestamp":1732257708000},"page":"1006","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":2,"title":["Advancing Continuous Distribution Generation: An Exponentiated Odds Ratio Generator Approach"],"prefix":"10.3390","volume":"26","author":[{"given":"Xinyu","family":"Chen","sequence":"first","affiliation":[{"name":"Department of Mathematics and Statistics, University of West Florida, Pensacola, FL 32514, USA"},{"name":"Department of Epidemiology, Biostatistics and Occupational Health, McGill University, Montreal, QC H3A 0C7, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zhenyu","family":"Shi","sequence":"additional","affiliation":[{"name":"Department of Communications Engineering, Zhejiang University of Science and Technology, Hangzhou 310018, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yuanqi","family":"Xie","sequence":"additional","affiliation":[{"name":"Department of Computer Science, University of West Florida, Pensacola, FL 32514, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Zichen","family":"Zhang","sequence":"additional","affiliation":[{"name":"Department of Mathematical and Computational Sciences, University of Toronto Mississauga, Mississauga, ON L5L 1C6, Canada"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-7843-4517","authenticated-orcid":false,"given":"Achraf","family":"Cohen","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, University of West Florida, Pensacola, FL 32514, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0148-1734","authenticated-orcid":false,"given":"Shusen","family":"Pu","sequence":"additional","affiliation":[{"name":"Department of Mathematics and Statistics, University of West Florida, Pensacola, FL 32514, USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2024,11,22]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Rodr\u00edguez Gonz\u00e1lez, C.A., Rodr\u00edguez-P\u00e9rez, A.M., L\u00f3pez, R., Hern\u00e1ndez-Torres, J.A., and Caparr\u00f3s-Mancera, J.J. 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