Results 11 to 20 of about 2,495,910 (283)

On the Performance of Principal Component Liu-Type Estimator under the Mean Square Error Criterion [PDF]

open access: yesJournal of Applied Mathematics, 2013
Wu (2013) proposed an estimator, principal component Liu-type estimator, to overcome multicollinearity. This estimator is a general estimator which includes ordinary least squares estimator, principal component regression estimator, ridge estimator, Liu ...
Jibo Wu
doaj   +2 more sources

Superiority of the Stochastic Restricted Liu Estimator under misspecification

open access: yesStatistica, 2007
This paper deals with the use of correct prior infromation in the estimation of regression coefficients when the regression model is misspecified due to the exclusion of some relevant regressor variables.
M. H. Hubert, Pushba Wijekoon
doaj   +2 more sources

Efficiency of a Liu-type estimator in semiparametric regression models

open access: yesJournal of Computational and Applied Mathematics, 2011
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Esra Akdeniz Duran   +2 more
core   +6 more sources

The Liu-Type Estimator Based on Parameter Optimization and its Application in SBAS Deformation Model Inversion

open access: yesIEEE Access, 2021
A situation in which an image is combined with multiple images to form interferometric pairs is often observed in small baseline subset-interferometric synthetic aperture radar (SBAS-InSAR) deformation inversion, and this situation leads to a near linear
Min Zhai   +6 more
doaj   +2 more sources

Modified One-Parameter Liu Estimator for the Linear Regression Model

open access: yesModelling and Simulation in Engineering, 2020
Motivated by the ridge regression (Hoerl and Kennard, 1970) and Liu (1993) estimators, this paper proposes a modified Liu estimator to solve the multicollinearity problem for the linear regression model.
Adewale F. Lukman   +3 more
doaj   +2 more sources

New Restricted Liu Estimator in a Partially Linear Model

open access: yesDiscrete Dynamics in Nature and Society, 2020
In this paper, we introduce a new restricted Liu estimator in a partially linear model when addition linear constraints are assumed to hold. We also consider the asymptotic normality of the new estimator.
Jibo Wu, Yong Li
doaj   +2 more sources

Shifted Liu-Type Estimator in The Linear Regression [PDF]

open access: yes, 2022
The methods to solve the problem of multicollinearity have an important issue in the linear regression. The Liu-type estimator is one of these methods used to reduce its effect. This estimator is an estimator with two parameters denoted  and . Kurnaz and
Erdugan, Funda
core   +1 more source

Liu-type shrinkage estimations in linear models

open access: yesStatistics, 2022
In this study, we present the preliminary test, Stein-type and positive part Liu estimators in the linear models when the parameter vector $\boldsymbolβ$ is partitioned into two parts, namely, the main effects $\boldsymbolβ_1$ and the nuisance effects $\boldsymbolβ_2$ such that $\boldsymbolβ=\left(\boldsymbolβ_1, \boldsymbolβ_2 \right)$.
Bahadır Yüzbaşı   +2 more
openaire   +2 more sources

A new biased regression estimator: Theory, simulation and application

open access: yesScientific African, 2022
The linear regression model explores the relationship between a response variable and one or more independent variables. The ordinary least squared estimator is usually adopted to estimate the parameters of the model when the independent variables are ...
Issam Dawoud   +2 more
doaj   +1 more source

Modified Kibria-Lukman (MKL) estimator for the Poisson Regression Model: application and simulation [version 2; peer review: 2 approved, 1 approved with reservations]

open access: yesF1000Research, 2021
Background: Multicollinearity greatly affects the Maximum Likelihood Estimator (MLE) efficiency in both the linear regression model and the generalized linear model. Alternative estimators to the MLE include the ridge estimator, the Liu estimator and the
Olukayode Adebimpe   +4 more
doaj   +1 more source

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