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

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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. 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

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

   www.sciencedirect.com › science › article

   Mar 1, 2023 · In this paper, we proposed an extended version of the Kibria–Lukman estimator (COMPKL estimator) to the Conway–Maxwell Poisson regression model to reduce the effect of the multicollinearity problem.

4. 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...

5. 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.

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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   Does Kibria-Lukman estimator reduce multicollinearity?

   • In this paper, we proposed an extended version of the Kibria–Lukman estimator (COMPKL estimator) to the Conway–Maxwell Poisson regression model to reduce the effect of the multicollinearity problem. We demonstrated that our proposed estimator is more efficient than previous biased estimators proposed in the literature (ridge and Liu estimators).

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

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

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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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   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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   How did kaciranlar & sakallioglu propose R D estimator?

   • Kaciranlar and Sakallioglu 9 proposed r–d estimator by combining Liu estimator and principal component estimator. Ozkale and Kaciranlar 10 proposed two parameter estimator by combining the James–Stein Shrinkage estimator and the modified ridge estimator proposed by Swindel.

   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...