Results 1 to 10 of about 103 (71)

On the mixed Kibria–Lukman estimator for the linear regression model

Scientific Reports, 2022
This paper considers a linear regression model with stochastic restrictions,we propose a new mixed Kibria–Lukman estimator by combining the mixed estimator and the Kibria–Lukman estimator.This new estimator is a general estimation, including OLS ...
Hongmei Chen, Jibo Wu
doaj   +4 more sources

Generalized Kibria-Lukman Estimator: Method, Simulation, and Application

Frontiers in Applied Mathematics and Statistics, 2022
In the linear regression model, the multicollinearity effects on the ordinary least squares (OLS) estimator performance make it inefficient. To solve this, several estimators are given. The Kibria-Lukman (KL) estimator is a recent estimator that has been
Issam Dawoud, Mohamed R. Abonazel, Fuad A. Awwad   +2 more
doaj   +4 more sources

Kibria–Lukman estimator for the Conway–Maxwell Poisson regression model: Simulation and applications

Scientific African, 2023
The Conway–Maxwell Poisson (COMP) regression model is one of the count data models to account for over– and under–dispersion. In regression analysis, when the explanatory variables are correlated, when there is multicollinearity problem, this inflates ...
Mohamed R. Abonazel, Ashrakat Adel Saber, Fuad A. Awwad   +2 more
doaj   +4 more sources

Combating outliers and multicollinearity in linear regression model using robust Kibria-Lukman mixed with principal component estimator, simulation and computation

Scientific African, 2023
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 ...
K.C. Arum, F.I. Ugwuowo, H.E. Oranye, T.O. Alakija, T.E. Ugah, O.C. Asogwa   +5 more
doaj   +4 more sources

Kibria–Lukman-Type Estimator for Regularization and Variable Selection with Application to Cancer Data

Mathematics, 2023
Following the idea presented with regard to the elastic-net and Liu-LASSO estimators, we proposed a new penalized estimator based on the Kibria–Lukman estimator with L1-norms to perform both regularization and variable selection.
Adewale Folaranmi Lukman, Jeza Allohibi, Segun Light Jegede, Emmanuel Taiwo Adewuyi, Segun Oke, Abdulmajeed Atiah Alharbi   +5 more
doaj   +4 more sources

Modified Kibria-Lukman (MKL) estimator for the Poisson Regression Model: application and simulation [version 2; peer review: 2 approved, 1 approved with reservations] [PDF]

F1000Research, 2021
Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear model. Alternative estimators to the MLE include the ridge estimator, the Liu estimator and the
Olukayode Adebimpe, Benedicta B. Aladeitan, Adewale F. Lukman, Oluwakemi E. Abiodun, Olajumoke Oludoun   +4 more
doaj   +9 more sources

Modified Kibria–Lukman Estimator for the Conway–Maxwell–Poisson Regression Model: Simulation and Application

Mathematics
This study presents a novel estimator that combines the Kibria–Lukman and ridge estimators to address the challenges of multicollinearity in Conway–Maxwell–Poisson (COMP) regression models.
Nasser A. Alreshidi, Masad A. Alrasheedi, Adewale F. Lukman, Hleil Alrweili, Rasha A. Farghali   +4 more
doaj   +4 more sources

Jackknife Kibria-Lukman M-Estimator: Simulation and Application

Journal of Nigerian Society of Physical Sciences, 2022
The ordinary least square (OLS) method is very efficient in estimating the regression parameters in a linear regression model under classical assumptions.
Segun L. Jegede, Adewale F. Lukman, Kayode Ayinde, Kehinde A. Odeniyi   +3 more
doaj   +2 more sources

K-L Estimator: Dealing with Multicollinearity in the Logistic Regression Model

Mathematics, 2023
Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and Lukman estimator (KLE) was developed as an alternative to the MLE to handle multicollinearity ...
Adewale F. Lukman, B. M. Golam Kibria, Cosmas K. Nziku, Muhammad Amin, Emmanuel T. Adewuyi, Rasha Farghali   +5 more
doaj   +5 more sources

Kibria–Lukman Hybrid Estimator for Handling Multicollinearity in Poisson Regression Model: Method and Application

International Journal of Mathematics and Mathematical Sciences
The Poisson regression model (PRM) is a widely used statistical technique for analyzing count data. However, when explanatory variables in the model are correlated, the estimation of regression coefficients using the maximum likelihood estimator (MLE ...
Hleil Alrweili
doaj   +3 more sources