Estimation in covariate-adjusted regression

We propose a new estimation procedure for covariate adjusted nonlinear regression models for situations where both the predictors and response in a nonlinear regression model are not directly observed, however distorted versions of the predictors and response are observed. The distorted versions are assumed to be contaminated with a multiplicative factor that is determined by the value of an unknown function of an observable covariate. We demonstrate how the regression coefficients can be estimated by establishing a connection to nonlinear varyingcoefficient models. Simulation studies are used to illustrate the efficacy of the proposed estimation algorithm. Literature Review:CAR Consider the multiple regression model,