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1. • • 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.
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     Kibria–Lukman estimator for the Conway–Maxwell Poisson ...

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   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 Kibria-Lukman estimator solve multicollinearity problem?

   • 6. Some Concluding Remarks Kibria and Lukman (2020) developed the K-L estimator to circumvent the multicollinearity problem for the linear regression model. In this paper, we described the logistic Kibria-Lukman estimator (LKLE) to address the challenge of multicollinearity for the logistic regression model.

   K-L Estimator: Dealing with Multicollinearity in the Logistic ... - MDPI

   www.mdpi.com/2227-7390/11/2/340

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   What is a K-L estimator?

   • Recently the K-L estimator emerged as another estimator in the ridge class and the Liu estimator with a single biasing parameter class [ 10 ]. The K-L estimator is a form of the Liu-type estimator with one parameter that minimizes the residual sum of squares with respect to the L2 norm with a prior information.

   K-L Estimator: Dealing with Multicollinearity in the Logistic ... - MDPI

   www.mdpi.com/2227-7390/11/2/340

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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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3. 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.

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

   www.tandfonline.com › doi › full

   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.

5. www.mdpi.com › 2227/7390/12-18 › 2929Robust Negative Binomial Regression via the Kibria–Lukman ...

   www.mdpi.com › 2227/7390/12-18 › 2929

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   Sep 20, 2024 · This study addresses the challenges of multicollinearity and outliers in NBR by integrating Ridge and Kibria–Lukman estimators with robust estimators, resulting in new hybrid estimators termed M-NBRRE and M-NBKLE.

6. 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 proposed, along...

7. www.tandfonline.com › doi › fullOn the preliminary test Kibria-Lukman estimator for the ...

   www.tandfonline.com › doi › full

   Aug 1, 2024 · Kibria and Lukman introduced the Kibria-Lukman estimator, which in some circumstances performs better than the ridge estimator. In this study, we combined the idea of the Kibria-Lukman estimator with the preliminary test method to produce the preliminary test Kibria-Lukman estimator (PTKLE).

8. www.mdpi.com › 2227/7390/11-2 › 340K-L Estimator: Dealing with Multicollinearity in the Logistic ...

   www.mdpi.com › 2227/7390/11-2 › 340

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   Jan 9, 2023 · Kibria and Lukman (2020) developed the K-L estimator to circumvent the multicollinearity problem for the linear regression model. In this paper, we described the logistic Kibria-Lukman estimator (LKLE) to address the challenge of multicollinearity for the logistic regression model.

9. 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 · In this paper, a new mixed KL estimator under stochastic restrictions is proposed, and its excellent properties under certain conditions are proved theoretically. The above theoretical results...