On an Adaptive Estimator of the Least Contrast in a Model with Nonlinear Functional Relations

Abstract

We consider an implicit nonlinear functional model with errors in variables. On the basis of the concept of deconvolution, we propose a new adaptive estimator of the least contrast of the regression parameter. We formulate sufficient conditions for the consistency of this estimator. We consider several examples within the framework of the L ₁- and L ₂-approaches.