Estimation in covariate-adjusted regression

Abstract

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,

DOI: 10.1016/j.csda.2005.06.001

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Cite this paper

@article{Sentrk2006EstimationIC, title={Estimation in covariate-adjusted regression}, author={Damla Sent{\"{u}rk and Danh V. Nguyen}, journal={Computational Statistics & Data Analysis}, year={2006}, volume={50}, pages={3294-3310} }