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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...

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 › 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...

4. 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.

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. link.springer.com › article › 10Combining Kibria-Lukman and principal component estimators ...

   link.springer.com › article › 10

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   Apr 11, 2023 · By integrating the principal component (PC) approach with the Almon Kibria-Lukman (KL) estimator, the Almon principal component Kibria-Lukman estimator is proposed in this paper. The new technique possesses the advantage of the principal component estimator and the Almon-KL estimator.

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 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

   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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   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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   Who proposed a two parameter estimator based on ridge estimator and Liu estimator?

   • Yang and Chang 12 proposed another two parameter estimator based on ridge estimator and Liu estimator. Lukman et al. 13 proposed a new estimator by combining modified ridge estimator (MRT) and principal component estimator. Kibria and Lukman 14 proposed Kibria–Lukman estimator by combining ridge estimator and Liu estimator.

   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 · 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...