Yahoo Canada Web Search

Search results

1. 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,...

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

   www.frontiersin.org › journals › applied-mathematics

   • Cached

   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.

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

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

   • Cached

   Sep 20, 2024 · Following the works of [15,16], Kibria and Lukman developed the Kibria–Lukman estimator (KLE), a single-parameter biased estimator designed to address multicollinearity in linear regression models. They demonstrated that this estimator outperforms both the Ridge and Liu estimators in terms of estimation accuracy and stability.

4. www.academia.edu › 88400166 › Generalized_Kibria(PDF) Generalized Kibria-Lukman Estimator: Method, Simulation ...

   www.academia.edu › 88400166 › Generalized_Kibria

   • Cached

   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.

5. www.researchgate.net › publication › 360932190(PDF) Jackknife Kibria-Lukman M-Estimator: Simulation and ...

   www.researchgate.net › publication › 360932190

   May 29, 2022 · This study proposed the Robust Jackknife Kibria-Lukman (RJKL) estimator based on the M-estimator to deal with multicollinearity and outliers. We examine the superiority of the estimator...

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

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

   • Cached

   Jan 9, 2023 · Multicollinearity negatively affects the efficiency of the maximum likelihood estimator (MLE) in both the linear and generalized linear models. The Kibria and Lukman estimator (KLE) was developed as an alternative to the MLE to handle multicollinearity for the linear regression model.

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

   See all results for this question

   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

   See all results for this question

   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

   See all results for this question

   What are the different types of estimators?

   • These estimators include the Stein estimator by Stein (1956), the principal component estimator by Massy (1965), the ridge estimator by Hoerl and Kennard (1970), the Liu estimator by Liu (1993), and the Liu-type estimator by Liu (2003).

   (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

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

   Kibria and Lukman14 proposed the Kibria Lukman (KL) estimator: where k > 0 is the parameter.KL estimator is obtained by solving the following extreme value problem: where c is constant, k is the...