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- 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. The K-L estimator outperforms the RRE and Liu estimators based on the theoretical conditions.
www.mdpi.com/2227-7390/11/2/340K-L Estimator: Dealing with Multicollinearity in the Logistic ...
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What is the Kibria-Lukman estimator?
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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.
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.
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,...
Dec 12, 2023 · Since, under multicollinearity, the widely used maximum likelihood estimator becomes unstable, this article proposes an alternative estimator, called Kibria–Lukman estimator for the zero inflated negative binomial model and provided some new biasing parameters.
α′[W2M2 −Ip]′[V1 +(W2G−Ip)αα′(W2G−Ip)′] [W2M2 −Ip]α < 1 (20) λ−1max (21) where V1 = σ2(W2GW2′ − W2M2G−1M2′W2′), N = W2KG−1KW2′, and M = 2W2KKW2′. Proof: V1 ...
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.
Feb 28, 2024 · The Preliminary Test Kibria-Lukman Estimator (PTKLE), which is based on the Wald (W), Likelihood Ratio (LR), and Lagrangian Multiplier (LM) tests, is offered in this study when it is believed that the regression parameter may be restricted to a subspace.
