A Simulation Study of Some Ridge Estimators
- 1 March 1981
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 76 (373) , 131
- https://doi.org/10.2307/2287058
Abstract
Ridge regression, which defines a class of estimators indexed by a biasing parameter k, is an alternative to least squares estimation in the multiple linear regression model. Many algorithms for the biasing parameter have been proposed in the statistical literature. The present study identifies 10 promising algorithms and systematically evaluates and compares them using Monte Carlo methods. Three algorithms perform well overall. A two-parameter estimator offers potential improvement over one-parameter ridge estimators.Keywords
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