TY - JOUR
T1 - Empirical Examination of the Poisson Regression Residuals for the Evaluation of Influential Points
AU - Khan, Aamna
AU - Ullah, Muhammad Aman
AU - Amin, Muhammad
AU - Muse, Abdisalam Hassan
AU - Aldallal, Ramy
AU - Mohamed, Mohamed S.
N1 - Publisher Copyright:
© 2022 Aamna Khan et al.
PY - 2022
Y1 - 2022
N2 - A common practice is to get reliable regression results in the generalized linear model which is the detection of influential cases. For the identification of influential cases, the present study focuses to compare empirically the performance of various existing residuals for the case of the Poisson regression model. Furthermore, we computed Cook's distance for the stated residuals. In order to show the effectiveness of proposed methodology, data have been generated by using simulation, and further applicability of methodology is shown with the help of real data that followed the Poisson regression. The comparative analysis of the residuals is carried out for the detection of influential cases.
AB - A common practice is to get reliable regression results in the generalized linear model which is the detection of influential cases. For the identification of influential cases, the present study focuses to compare empirically the performance of various existing residuals for the case of the Poisson regression model. Furthermore, we computed Cook's distance for the stated residuals. In order to show the effectiveness of proposed methodology, data have been generated by using simulation, and further applicability of methodology is shown with the help of real data that followed the Poisson regression. The comparative analysis of the residuals is carried out for the detection of influential cases.
UR - http://www.scopus.com/inward/record.url?scp=85131180416&partnerID=8YFLogxK
U2 - 10.1155/2022/6995911
DO - 10.1155/2022/6995911
M3 - Article
AN - SCOPUS:85131180416
SN - 1024-123X
VL - 2022
JO - Mathematical Problems in Engineering
JF - Mathematical Problems in Engineering
M1 - 6995911
ER -