Partial index additive models with additive distortion measurement errors

Abstract

This paper considers the estimation for a partial index additive regression model, when the response variable and covariates in the index part are observed with additive distortion measurement errors. For the index parameter, the dimension-reduction based estimators with or without additive distortion measurement errors are proposed. This new estimation method is further adopted to the partial linear models for parameter estimation. We study the asymptotic properties of the proposed estimators. Simulation studies are conducted to compare the proposed estimation methods.