Results 21 to 30 of about 197,245 (124)

Performance of some estimators for the multicollinear logistic regression model: theory, simulation, and applications

Research in Statistics
This article proposes some new estimators, namely Stein’s estimators for ridge regression and Kibria and Lukman estimator and compares their performance with some existing estimators, namely maximum likelihood estimator (MLE), ridge regression estimator,
Md Ariful Hoque, B. M. Golam Kibria
doaj   +2 more sources

The Efficiency of the K-L Estimator for the Seemingly Unrelated Regression Model: Simulation and Application

Journal of Nigerian Society of Physical Sciences, 2023
This paper considers the Ridge Feasible Generalized Least Squares Estimator (RFGLSE), Ridge Seemingly Unrelated Regression RSUR and proposes the Kibria-Lukman KLSUR estimator for the parameters of the Seemingly Unrelated Regression (SUR) model when the ...
Oluwayemisi Oyeronke Alaba, B. M. Golam Kibria   +1 more
doaj   +2 more sources

Special ridge-type estimator: Simulation and application to chemical data

AIP Advances
This study delves into regularization techniques, such as ridge regression, Liu estimator, and Kibria–Lukman estimator, as alternatives to the maximum likelihood method for addressing multicollinearity in beta regression models.
Rasha A. Farghali, Adewale F. Lukman, Haadi Abdul-Rahaman, Zakariya Yahya Algamal, Samah M. Abo-El-Hadid   +4 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   +2 more sources

Dawoud–Kibria Estimator for Beta Regression Model: Simulation and Application

Frontiers in Applied Mathematics and Statistics, 2022
The linear regression model becomes unsuitable when the response variable is expressed as percentages, proportions, and rates. The beta regression (BR) model is more appropriate for the variable of this form.
Mohamed R. Abonazel, Issam Dawoud, Fuad A. Awwad, Adewale F. Lukman   +3 more
doaj   +2 more sources

A Poisson-modified quasi-lindley regression approach for multicollinear data using Kibria–Lukman Estimator

Scientific African
Count regression models based on the Poisson distribution are widely used for non‑negative integer responses but often perform poorly when data exhibit overdispersion and multicollinearity, leading to inflated variances and unstable maximum likelihood ...
Rikan A. Ahmed, Zakariya Yahya Algamal, Liban Ali Mohamud   +2 more
doaj   +2 more sources

Efficiency of a hybrid Kibria–Lukman estimator in the Cox regression model with survival data application

Hacettepe Journal of Mathematics and Statistics
This paper develops and evaluates a new hybrid Kibria–Lukman estimator for the Cox regression model to more effectively handle severe multicollinearity in survival data. The Cox model is widely used for time data analysis, but strong linear dependencies among covariates make the maximum likelihood estimator unstable, inflating variance and mean squared
Zakariya Yahya Algamal
openaire   +2 more sources

Combining Kibria-Lukman and principal component estimators for the distributed lag models

Behaviormetrika, 2023
Mina Norouzirad
exaly   +2 more sources

Quantile-based robust Kibria–Lukman estimator for linear regression model to combat multicollinearity and outliers: Real life applications using T20 cricket sports and anthropometric data

Kuwait Journal of Science
The performance of ordinary least squares (OLS) and ridge regression (RR) are influenced when outliers are present in y-direction with multicollinearity among independent variables. The robust RR with ridge parameters provides a biased estimator that has
Danish Wasim, Muhammad Suhail, Sajjad Ahmad Khan, Maha Shabbir, Fuad A. Awwad, Emad A.A. Ismail, Hijaz Ahmad, Amjad Ali   +7 more
doaj   +2 more sources