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
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
doaj +3 more sources
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
doaj +2 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 +4 more
doaj +2 more sources
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
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.
europepmc +2 more sources
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 +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 +2 more
doaj +3 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
doaj +2 more sources