TITLE:
Orthogonal Series Estimation of Nonparametric Regression Measurement Error Models with Validation Data
AUTHORS:
Zanhua Yin
KEYWORDS:
Ill-Posed Inverse Problems, Measurement Errors, Nonparametric Regression, Orthogonal Series, Validation Data
JOURNAL NAME:
Applied Mathematics,
Vol.8 No.12,
December
29,
2017
ABSTRACT:
In this article we study the estimation method of nonparametric regression
measurement error model based on a validation data. The estimation procedures
are based on orthogonal series estimation and truncated series approximation
methods without specifying any structure equation and the distribution
assumption. The convergence rates of the proposed estimator are derived.
By example and through simulation, the method is robust against the
misspecification of a measurement error model.