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<p>This paper introduces a novel regression model based on the Exponentiated Normal (Exp-N) distribution and compares its performance with traditional Normal regression. Using the maximum likelihood method, parameters for both the regression structure and the underlying distributions were estimated. The Exp-N regression model was thoroughly investigated, with several new statistical properties derived and validated. Applied to a real-world dataset of testosterone hormone levels, the model demonstrated superior goodness-of-fit over the conventional Normal regression, offering a more flexible and accurate framework for data analysis in medical and biological research.</p>

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The Exponentiated Normal Regression Model with Application

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月18日

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  • Eman Madkour,
  • Salah Mahdy,
  • Amal Abdel Fattah

摘要

This paper introduces a novel regression model based on the Exponentiated Normal (Exp-N) distribution and compares its performance with traditional Normal regression. Using the maximum likelihood method, parameters for both the regression structure and the underlying distributions were estimated. The Exp-N regression model was thoroughly investigated, with several new statistical properties derived and validated. Applied to a real-world dataset of testosterone hormone levels, the model demonstrated superior goodness-of-fit over the conventional Normal regression, offering a more flexible and accurate framework for data analysis in medical and biological research.