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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).
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.
Apr 1, 2022 · In this study, we proposed a hybrid estimator by combining the Kibria-Lukman estimator with the modified ridge-type estimator. The proposed estimator theoretically dominates the existing...
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...
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.
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.
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What is the Kibria-Lukman estimator?
What is Kibria Lukman (KL) estimator?
Does Kibria-Lukman estimator reduce multicollinearity?
What is a jackknife Kibria-Lukman estimator?
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.