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 +4 more
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On the mixed Kibria–Lukman estimator for the linear regression model [PDF]
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
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A New Ridge-Type Estimator for the Gamma Regression Model. [PDF]
Scientifica (Cairo), 2021 The known linear regression model (LRM) is used mostly for modelling the QSAR relationship between the response variable (biological activity) and one or more physiochemical or structural properties which serve as the explanatory variables mainly when ...
Lukman AF +4 more
europepmc +4 more sources
International Journal of Mathematics and Mathematical SciencesThe 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
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Kibria-Lukman Estimator for General Linear Regression Model with AR(2) Errors: A Comparative Study with Monte Carlo Simulation [PDF]
Journal of New Theory, 2022 The sensitivity of the least-squares estimation in a regression model is impacted by multicollinearity and autocorrelation problems. To deal with the multicollinearity, Ridge, Liu, and Ridge-type biased estimators have been presented in the statistical ...
Tuğba Söküt Açar
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A new estimator for the multicollinear Poisson regression model: simulation and application. [PDF]
Sci Rep, 2021 The maximum likelihood estimator (MLE) suffers from the instability problem in the presence of multicollinearity for a Poisson regression model (PRM).
Lukman AF +3 more
europepmc +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 +3 more
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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 +2 more
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Predictive modelling of COVID-19 confirmed cases in Nigeria. [PDF]
Infect Dis Model, 2020 The coronavirus outbreak is the most notable world crisis since the Second World War. The pandemic that originated from Wuhan, China in late 2019 has affected all the nations of the world and triggered a global economic crisis whose impact will be felt ...
Ogundokun RO +4 more
europepmc +6 more sources
A New Ridge-Type Estimator for the Linear Regression Model: Simulations and Applications. [PDF]
Scientifica (Cairo), 2020 The ridge regression‐type (Hoerl and Kennard, 1970) and Liu‐type (Liu, 1993) estimators are consistently attractive shrinkage methods to reduce the effects of multicollinearity for both linear and nonlinear regression models. This paper proposes a new estimator to solve the multicollinearity problem for the linear regression model.
Kibria BMG, Lukman AF.
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