Improved Liu estimator in a linear regression model

DOI10.1016/J.JSPI.2010.05.030zbMath1197.62058OpenAlexW2075938582MaRDI QIDQ151048

Xu-Qing Liu, Xu-Qing Liu

Publication date: January 2011

Published in: Journal of Statistical Planning and Inference (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.jspi.2010.05.030

zbMATH Keywords

PRESS criterion

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Linear regression; mixed models (62J05)

Related Items (8)

On the Liu estimator in the beta and Kumaraswamy regression models: A comparative study ⋮ General linear estimators under the prediction error sum of squares criterion in a linear regression model ⋮ Improved ridge estimators in a linear regression model ⋮ Non-Diagonal-Type Estimator in Linear Regression ⋮ A Generalized Diagonal Ridge-type Estimator in Linear Regression ⋮ liureg ⋮ Positive-rule stein-type almost unbiased ridge estimator in linear regression model ⋮ SLASSO: a scaled LASSO for multicollinear situations

Cites Work

• Shrinkage structure in biased regression
• A new biased estimator based on ridge estimation
• An alternative stochastic restricted Liu estimator in linear regression
• Improvement of the Liu estimator in linear regression model
• On the Restricted Liu Estimator in the Gauss–Markov Model
• A Monte Carlo Evaluation of Some Ridge-Type Estimators
• Double k-Class Estimators of Coefficients in Linear Regression
• A new class of blased estimate in linear regression
• On the almost unbiased generalized liu estimator and unbiased estimation of the bias and mse
• COMBINING THE LIU ESTIMATOR AND THE PRINCIPAL COMPONENT REGRESSION ESTIMATOR
• The Relationship between Variable Selection and Data Agumentation and a Method for Prediction
• Using Liu-Type Estimator to Combat Collinearity
• Robust Liu estimator for regression based on an M-estimator
• A Prediction-Oriented Criterion for Choosing the Biasing Parameter in Liu Estimation
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
• Mean Square Error of Prediction as a Criterion for Selecting Variables

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