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  1. 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).

  2. 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. 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...

  4. 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...

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

  6. 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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  8. 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.

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