Transforming to Normality in Regression Analysis with Exponentially Residuals

Authors

  • Azad Adil Shareef Department of Statistics, University of Duhok, Kurdistan Region, Iraq
  • Haithem Taha Mohammed Ali Department of Economic Sciences, University of Zakho, Kurdistan Region, Iraq, and Department of Economics, Nawroz University, Kurdistan Region, Iraq

DOI:

https://doi.org/10.25007/ajnu.v12n4a1902

Abstract

In this article, a simulated study is introduced, focusing on the use of power transformation to estimate a nonlinear regression model in the presence of residuals following an exponential distribution. Four criteria were employed to estimate the power parameter: the p-value of Shapiro-Wilk test statistics for both the transformed and back-transformed data's normality, maximum likelihood estimation, and coefficient of determination. The findings of the study indicate that while it is possible to identify a range of viable solutions to select the optimal power parameter, finding a single optimal value that satisfies all estimation and decision methods is not feasible.

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Published

2023-10-14

How to Cite

Adil Shareef, A., & Mohammed Ali, H. T. (2023). Transforming to Normality in Regression Analysis with Exponentially Residuals . Academic Journal of Nawroz University, 12(4), 317–322. https://doi.org/10.25007/ajnu.v12n4a1902

Issue

Vol. 12 No. 4 (2023)

Section

Articles

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