167 – Special Issues in Modeling
Unique Regression Model for Both Symmetric and Asymmetric Regressed Variable
Mian Arif Shams Adnan
Department of Computer Science, Ball State University
Silvey Shamsi
Center for Business and Economic Research (CBER), Ball State University
Rahmatullah Imon
Department of Mathematical Sciences, Ball State University
All previously derived Regression Models were either based on the normality assumption(s) of the regressed variable and their non-normality counterparts on their asymmetric distributional assumption of the explained variable. The present paper addressed a new sort of common regression model that is suitable for error(s) either following a symmetric distribution or an asymmetric distribution. Attempt for estimation of parameters has also been addressed