Simulation study of new estimators combining the SUR ridge regression and the restricted least squares methodologies

DOI10.1007/s00362-008-0151-2zbMath1247.62176OpenAlexW2014790933MaRDI QIDQ451445

M. A. Alkhamisi

Publication date: 23 September 2012

Published in: Statistical Papers (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s00362-008-0151-2

zbMATH Keywords

Monte Carlo simulationsmulticollinearityLiu estimatorbiased estimatorrestricted generalized least squares estimatorSUR restricted ridge estimator

Mathematics Subject Classification ID

Ridge regression; shrinkage estimators (Lasso) (62J07) Linear regression; mixed models (62J05) Monte Carlo methods (65C05)

Related Items (8)

Optimal estimator under risk matrix in a seemingly unrelated regression model and its generalized least squares expression ⋮ Modified Liu-Type Estimator Based on (r − k) Class Estimator ⋮ Modified Liu-Type Estimator Based on (r − k) Class Estimator ⋮ Ridge estimation in linear models with heteroskedastic errors ⋮ Multiple mediation analysis for interval-valued data ⋮ A Monte Carlo study on the ridge parameter of the seemingly unrelated ridge regression models ⋮ Local influence in seemingly unrelated regression model with ridge estimate ⋮ MODIFICATION OF LIU-TYPE ESTIMATOR FOR TWO SUR MODEL

Cites Work

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• A new class of blased estimate in linear regression
• Performance of Some New Ridge Regression Estimators
• Developing Ridge Parameters for SUR Model
• Ridge Regression: Biased Estimation for Nonorthogonal Problems
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• An Efficient Method of Estimating Seemingly Unrelated Regressions and Tests for Aggregation Bias

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