Minimax Adaptive Generalized Ridge Regression Estimators
- 1 September 1978
- journal article
- research article
- Published by JSTOR in Journal of the American Statistical Association
- Vol. 73 (363) , 623
- https://doi.org/10.2307/2286612
Abstract
We consider the problem of estimating the vector of regression coefficients of a linear model using generalized ridge regression estimators where the ridge constant is chosen on the basis of the data. For general quadratic loss we produce such estimators whose risk function dominates that of the least squares procedure provided the number of regressors is at least three. We study the problem by the usual reduction to estimating the mean vector of a multivariate normal distribution. Our results on minimax estimation in this context are of independent interest.Keywords
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