On some ridge regression estimators: a nonparametric approach

A. Saleh and B. Golam Kibria

Journal of Nonparametric Statistics, 2011, vol. 23, issue 3, 819-851

Abstract: This paper considers the R-estimation of the parameters of a multiple regression model when the design matrix is ill-conditioned. Accordingly, we introduce the ridge regression (RR) modification to the usual R-estimators and consider five RR R-estimators when it is suspected that the regression parameters may belong to a linear subspace of the parameter space. The regions of optimality of the proposed estimators are determined based on the quadratic risks. Asymptotic relative efficiency tables and risk graphs are provided for the numerical and graphical comparisons of the five estimators.

Date: 2011
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DOI: 10.1080/10485252.2011.567335

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