Ridge estimation in semiparametric linear measurement error models

We consider the ridge and restricted ridge estimation in semiparametric linear models when the covariates are measured with errors and the covariance matrix of the parameters is ill conditioned. The estimators are compared and the dominance conditions as well as the regions of optimality of the proposed estimators are determined based on quadratic risks. A simulation studies are conducted to illustrate the finite sample performance of the proposed procedures.