New Method for Generating Continuous Statistical Distributions
Author Information
Author(s): Chen Xinyu, Shi Zhenyu, Xie Yuanqi, Zhang Zichen, Cohen Achraf, Pu Shusen
Primary Institution: Department of Mathematics and Statistics, University of West Florida
Hypothesis
Can the exponentiated odds ratio be effectively integrated into survival analysis to create a new family of continuous distributions?
Conclusion
The proposed Type 2 Gumbel Weibull-G family of distributions demonstrates superior statistical accuracy and flexibility in modeling complex datasets compared to traditional models.
Supporting Evidence
- The new generator enhances the flexibility and adaptability of distribution models.
- Real-world applications demonstrate the statistical precision of the new distributions.
- The study provides a comprehensive analysis of the mathematical properties of the proposed distributions.
Takeaway
This study introduces a new way to create statistical models that can better handle complicated data, making it easier to understand and predict outcomes.
Methodology
The study employs a new generator based on the exponentiated odds ratio, tested through five distinct parameter estimation methods and applied to three real-world datasets.
Limitations
The complexity of the new distributions may pose challenges in practical applications and understanding.
Digital Object Identifier (DOI)
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