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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.
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.
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...
Dec 14, 2021 · MSE(βˆPLE)= ∑P j=1 (λj + d)2 λj(λj + 1)2 + (d − 1)2 ∑p j−1 α2j (λj + 1)2. (2.9) where λj is the j th eigenvalue of X′LˆX and α j is the j th element of α. The KL estimator was proposed by Kibria and Lukman (2020) as a means of mitigating the effect of multicollinearity on parameter estimation.
Consider the following linear regression model: y = Xβ + ε, (1) where y is the response variable vector of n × 1,X. n × (p + 1),β is the unknown coeficient vector of E(ε) = 0 and Cov(ε) = σ2I ,...
Jul 20, 2022 · 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...
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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?
Is KL estimator better than mixed estimator?
Does a mixed KL estimator have a minimum MSE?
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.
