JSM 2003 Online Program

Abstract #300168

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Activity Number:	207
Type:	Contributed
Date/Time:	Tuesday, August 5, 2003 : 8:30 AM to 10:20 AM
Sponsor:	IMS
Abstract - #300168
Title:	Structural Nonlinear Measurement Error Models with Replicates
Author(s):	Daniela Cojocaru*+ and Nicolas Hengartner
Companies:	Yale University and Los Alamos National Laboratory
Address:	141 York St. Apt 9, New Haven, CT, 06511,
Keywords:	structural measurement error models ; asymptotics ; M-estimator ; nonlinear regression function
Abstract:	This talk introduces a new M-estimator for parametric nonlinear structural measurement error models (also known as errors-in-variables models) when replicates for the mismeasured covariate are available. Our method does not assume knowledge of the distribution of the additive error on the covariates. We give regularity conditions under which the estimate is consistent and satisfies a central limit theorem at the usual parametric rate. Simulations show that this estimator has good finite sample performance as well.

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