Search results
- As an alternative to the ridge and Liu estimators, Kibria and Lukman proposed new ridge–type estimator to resolve the issue of multicollinearity in the linear regression model. This estimator is called the Kibria–Lukman (KL) estimator.
People also ask
What is Kibria Lukman (KL) estimator?
What is the Kibria-Lukman estimator?
Does Kibria-Lukman estimator reduce multicollinearity?
What is a jackknife Kibria-Lukman estimator?
Mar 1, 2023 · As an alternative to the ridge and Liu estimators, Kibria and Lukman [16] proposed new ridge–type estimator to resolve the issue of multicollinearity in the linear regression model. This estimator is called the Kibria–Lukman (KL) 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.
called the Kibria–Lukman (KL) estimator which is defined by βˆKL = (X′X +kIp)−1(X′X −kIp)βˆ,k > 0 This estimator has been extended for use in different generalized linear models, such as Lukman et al. [4, 5], Akram et al. [6], and Abonazel et al. [7]. According to recent papers [8–10], we can say that the efficiency of any ...
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...
Kibria and Lukman14 proposed the Kibria Lukman (KL) estimator: where k > 0 is the parameter.KL estimator is obtained by solving the following extreme value problem: where c is...
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...
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.