Estimation Methods of Kumaraswamy Lindley Regression Model with Applications on Egyptian Stock Exchange Data

S.A. Mohamed¹ , S.M. Mohamed²

Section:Research Paper, Product Type: Journal-Paper
Vol.9 , Issue.1 , pp.19-23, Feb-2022

Online published on Feb 28, 2022

Copyright © S.A. Mohamed, S.M. Mohamed . This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
 

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Abstract :
In this paper, we present the different methods for estimating the parameters of the Kumaraswamy Lindley Regression Model using different methods, which are, respectively, Maximum Likelihood Estimation, Ordinary least-squares estimators, The weighted least squares(WLSE), Cramer-Von-Mises estimation, Method of Anderson-Darling, These methods were compared using each of the following statistical measures An Akaike information criterion (AIC), Consistent Akaike information criterion(CAIC), Bayesian information criterion(BIC), The application was carried out on data from the Egyptian Stock Exchange, The paper concluded that the method of the Maximum Likelihood Estimation was lower in value than each of the previous measures, and thus it is the best in

Key-Words / Index Term :
Kumaraswamy Lindley Regression, Maximum Likelihood Estimation(MLE). Ordinary least-squares estimators (OLS), weighted least squares(WLSE), Cramer-Von-Mises estimation (CVM), Method of Anderson-Darling

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