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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.tandfonline.com › doi › fullOn the jackknife Kibria-Lukman estimator for the linear ...

   www.tandfonline.com › doi › full

   Nov 26, 2021 · In this paper, we developed a Jackknifed version of the Kibria-Lukman estimator- the estimator is named the Jackknifed KL estimator (JKLE). We derived the statistical properties of the new estimator and compared it theoretically with the KLE and some other existing estimators.

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

   www.researchgate.net › publication › 360095086

   Apr 1, 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...

4. 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

5. 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.

6. 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...

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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   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

   See all results for this question

   Is KL estimator better than mixed estimator?

   • The necessary and sufficient conditions for KL estimator to be better than mixed estimator, KL estimator, OLS estimator and mixed ridge estimator under the criterion of mean square error matrix are given, and the proofs are given respectively. Then the theoretical results are verified by examples and simulation analysis.

   On the mixed Kibria–Lukman estimator for the linear ... - Nature

   www.nature.com/articles/s41598-022-16689-z

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   What is a jackknife Kibria-Lukman estimator?

   • On the jackknife Kibria-Lukman estimator .... The linear regression model explores the relationship between the dependent variable and the independent variables. The ordinary least squared estimator (OLSE) is widely applicable to estimate the parameters of the model.

   On the jackknife Kibria-Lukman estimator for the linear regression

   www.tandfonline.com/doi/full/10.1080/03610918.2021.2007401

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   Does a mixed KL estimator have a minimum MSE?

   • The new estimator mixed KL estimator always has the minimum MSE when all given n and \ (\sigma ^ {2}\) ,and k takes \ (\hat {k}_ {\min }\).

   On the mixed Kibria–Lukman estimator for the linear ... - Nature

   www.nature.com/articles/s41598-022-16689-z

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8. www.nature.com › articles › s41598/022/16689-zOn the mixed Kibria–Lukman estimator for the linear ...

   www.nature.com › articles › s41598/022/16689-z

   Jul 20, 2022 · Ozbay and Kaciranlar 20 integrated two parameter estimator and mixed estimator and proposed a two parameter mixed estimator. In this paper, a new mixed KL estimator under stochastic...