Combating outliers and multicollinearity in linear regression model using robust Kibria-Lukman mixed with principal component estimator, simulation and computation
Scholars usually adopt the method of least squared to model the relationship between a response variable and two or more explanatory variables. Ordinary least squares estimator's performance is good when there is no outliers and multicollinearity in the regression model dataset. Outliers and mu...
Main Authors: | K.C. Arum, F.I. Ugwuowo, H.E. Oranye, T.O. Alakija, T.E. Ugah, O.C. Asogwa |
---|---|
Format: | Article |
Language: | English |
Published: |
Elsevier
2023-03-01
|
Series: | Scientific African |
Subjects: | |
Online Access: | http://www.sciencedirect.com/science/article/pii/S246822762300025X |
Similar Items
-
Kibria–Lukman estimator for the Conway–Maxwell Poisson regression model: Simulation and applications
by: Mohamed R. Abonazel, et al.
Published: (2023-03-01) -
K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model
by: Adewale F. Lukman, et al.
Published: (2023-01-01) -
Robust modified jackknife ridge estimator for the Poisson regression model with multicollinearity and outliers
by: Kingsley C Arum, et al.
Published: (2022-09-01) -
New Robust Estimators for Handling Multicollinearity and Outliers in the Poisson Model: Methods, Simulation and Applications
by: Issam Dawoud, et al.
Published: (2022-11-01) -
A New Effective Jackknifing Estimator in the Negative Binomial Regression Model
by: Tuba Koç, et al.
Published: (2023-11-01)