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1. www.frontiersin.org › journals › applied-mathematicsFrontiers | Generalized Kibria-Lukman Estimator: Method ...

   www.frontiersin.org › journals › applied-mathematics

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   The Kibria-Lukman (KL) estimator is a recent estimator that has been proposed to solve the multicollinearity problem. In this paper, a generalized version of the KL estimator is proposed, along with the optimal biasing parameter of our proposed estimator derived by minimizing the scalar mean squared error.

2. www.sciencedirect.com › science › articleKibria–Lukman estimator for the Conway–Maxwell Poisson ...

   www.sciencedirect.com › science › article

   Mar 1, 2023 · In regression analysis, when the explanatory variables are correlated, when there is multicollinearity problem, this inflates the standard error of the maximum likelihood estimates. The Kibria–Lukman estimator was provided to handle the effect of multicollinearity in the linear regression model.

3. f1000research.com › articles › 10-548Modified Kibria-Lukman (MKL) estimator for the... | F1000Research

   f1000research.com › articles › 10-548

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   Jul 8, 2021 · In this study, we propose the Modified Kibria-Lukman estimator to handle multicollinearity in PRM. The estimator is a single parameter estimator which makes it less computationally intensive as compared with the two-parameter estimators.

   • Author: Benedicta B. Aladeitan, Olukayode Adebimpe, Adewale F. Lukman, Olajumoke Oludoun, Oluwakemi E. Abiod...

   • Publish Year: 2021

4. www.researchgate.net › publication › 360095086(PDF) Generalized Kibria-Lukman Estimator: Method, Simulation ...

   www.researchgate.net › publication › 360095086

   Apr 1, 2022 · In this paper, a generalized version of the KL estimator is proposed, along with the optimal biasing parameter of our proposed estimator derived by minimizing the scalar mean squared error.

5. www.researchgate.net › publication › 360095086GeneralizedKibria-Lukman Estimator:Method,Simulation,and ...

   www.researchgate.net › publication › 360095086

   INTRODUCTION. The statistical consequences of multicollinearity are well-known in statistics for a linear regression model. Multicollinearity is known as the approximately linear dependency among...

6. www.semanticscholar.org › paper › Generalized-KibriaGeneralized Kibria-Lukman Estimator: Method, Simulation, and ...

   www.semanticscholar.org › paper › Generalized-Kibria

   Apr 20, 2022 · The Kibria-Lukman (KL) estimator is a recent estimator that has been proposed to solve the multicollinearity problem. In this paper, a generalized version of the KL estimator is proposed, along with the optimal biasing parameter of our proposed estimator derived by minimizing the scalar mean squared error.

7. People also ask

   What is the Kibria-Lukman estimator?

   • The Kibria-Lukman (KL) estimator is a recent estimator that has been proposed to solve the multicollinearity problem. In this paper, a generalized version of the KL estimator is proposed, along with the optimal biasing parameter of our proposed estimator derived by minimizing the scalar mean squared error.

   (PDF) Generalized Kibria-Lukman Estimator: Method, Simulation, and

   www.researchgate.net/publication/360095086_Generalized_Kibria-Lukman_Estimator_Method_Simulation_and_Application

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   What is Kibria Lukman (KL) estimator?

   • As an alternative to the ridge and Liu estimators, Kibria and Lukman proposed new ridge–type estimator to resolve the issue of multicollinearity in the linear regression model. This estimator is called the Kibria–Lukman (KL) estimator.

   Kibria–Lukman estimator for the Conway–Maxwell Poisson regression m…

   www.sciencedirect.com/science/article/pii/S2468227623000121

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   Can a Kibria-Lukman estimator solve a multicollinearity problem?

   • 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 proposed to solve the multicollinearity problem.

   (PDF) Generalized Kibria-Lukman Estimator: Method, Simulation, and

   www.researchgate.net/publication/360095086_Generalized_Kibria-Lukman_Estimator_Method_Simulation_and_Application

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   How is the performance of the proposed estimator compared with OLS?

   • Theoretically, the performance of the proposed estimator is compared with the OLS, the generalized ridge, the generalized Liu, and the KL estimators by the matrix mean squared error. Furthermore, a simulation study and the numerical example were performed for comparing the performance of the proposed estimator with the OLS and the KL estimators.

   (PDF) Generalized Kibria-Lukman Estimator: Method, Simulation, and

   www.researchgate.net/publication/360095086_Generalized_Kibria-Lukman_Estimator_Method_Simulation_and_Application

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   Does the compkl estimator outperform ml Ridge & Liu estimators?

   • Two life applications were analyzed to illustrate the performance of the COMPKL estimator. The results of the simulation study and applications indicated that the COMPKL estimator outperforms the ML, ridge, and Liu estimators, especially when the explanatory variables are highly correlated. No Conflict of interest is declared by the authors.

   Kibria–Lukman estimator for the Conway–Maxwell Poisson regression m…

   www.sciencedirect.com/science/article/pii/S2468227623000121

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8. www.academia.edu › 88400166 › Generalized_KibriaGeneralized Kibria-Lukman Estimator: Method, Simulation, and ...

   www.academia.edu › 88400166 › Generalized_Kibria

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   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