A Simulation Study of Some Ridge Estimators
作者： Diane Galarneau Gibbons
DOI: 10.1080/01621459.1981.10477619
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摘要: Abstract Ridge regression, which defines a class of estimators indexed by biasing parameter k, is an alternative to least squares estimation in the multiple linear regression model. Many algorithms for have been proposed statistical literature. The present study identifies 10 promising and systematically evaluates compares them using Monte Carlo methods. Three perform well overall. A two-parameter estimator offers potential improvement over one-parameter ridge estimators.
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