Results 11 to 20 of about 218 (135)

Two-Parameter Modified Ridge-Type M-Estimator for Linear Regression Model. [PDF]

ScientificWorldJournal, 2020
The general linear regression model has been one of the most frequently used models over the years, with the ordinary least squares estimator (OLS) used to estimate its parameter. The problems of the OLS estimator for linear regression analysis include that of multicollinearity and outliers, which lead to unfavourable results. This study proposed a two‐
Lukman AF, Ayinde K, Golam Kibria BM, Jegede SL.   +3 more
europepmc   +2 more sources

A Modified Two Parameter Estimator with Different Forms of Biasing Parameters in the Linear Regression Model [PDF]

African Scientific Reports, 2022
Despite its common usage in estimating the linear regression model parameters, the ordinary least squares estimator often suffers a breakdown when two or more predictor variables are strongly correlated.
Abiola T. Owolabi, Kayode Ayinde, Olusegun O. Alabi   +2 more
doaj   +3 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-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   +2 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   +2 more sources

New two parameter hybrid estimator for zero inflated negative binomial regression models [PDF]

Scientific Reports
The zero-inflated negative binomial regression (ZINBR) model is used for modeling count data that exhibit both overdispersion and zero-inflated counts. However, a persistent challenge in the efficient estimation of parameters within ZINBR models is the ...
Fatimah A. Almulhim, M. Nagy, Ali T. Hammad, A. H. Mansi, Getachew Tekle Mekiso, M. M. Abd El-Raouf   +5 more
doaj   +2 more sources

A New Biased Estimation Class to Combat the Multicollinearity in Regression Models: Modified Two--Parameter Liu Estimator [PDF]

Computational Journal of Mathematical and Statistical Sciences
The multicollinearity problem occurrence of the explanatory variables affects the least-squares (LS) estimator seriously in the regression models. The multicollinearity adverse effects on the LS estimation are also investigated by many authors.
Mohamed Reda Abonazel
doaj   +3 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   +2 more sources

An Alternative Estimator for Poisson–Inverse-Gaussian Regression: The Modified Kibria–Lukman Estimator

Algorithms
Poisson regression is used to model count response variables. The method has a strict assumption that the mean and variance of the response variable are equal, while, in practice, the case of overdispersion is common.
Rasha A. Farghali, Adewale F. Lukman, Zakariya Algamal, Murat Genc, Hend Attia   +4 more
doaj   +2 more sources

A New Kibria-Lukman-Type Estimator for Poisson Regression Models

Acta Infologica
One of the most important models for the analysis of count data is the Poisson Regression Model (PRM). The parameter estimates of the PRM are obtained by the Maximum Likelihood Estimator (MLE).
Cemal Çiçek, Kadri Ulaş Akay
doaj   +3 more sources