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Journal of Multivariate Analysis
Volume 18, Issue 2, April 1986, Pages 187-215
 
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doi:10.1016/0047-259X(86)90069-2    How to Cite or Link Using DOI (Opens New Window)
Copyright © 1986 Published by Elsevier Inc.

Second order asymptotics in nonlinear regression

Wolfgang H. Schmidt and S. Zwanzig

Humboldt-Universität, Berlin, DDR-1086, German Democratic Republic Institut für Mathematik, ADW der DDR, Berlin, DDR-1086, German Democratic Republic

Received 25 August 1983; 
Revised 30 January 1984. 
Communicated by J. Pfanzagl 
Available online 30 June 2004.

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Abstract

It is a well known part of statistical knowledge that first order asymptotically efficient procedures can be misleading for moderate sample sizes. Usually this is demonstrated for some popular special cases including numerical comparisons. Typically the situation is worse if nuisance parameters are present. In this paper we give second order asymptotically efficient tests, confidence regions, and estimators for the nonlinear regression model which are based on the least-squares estimator and the residual sum of squares.

Author Keywords: Nonlinear regression; Edgeworth expansion; second order asymptotics; hypothesis testing; median unbiased estimators; confidence regions

62J02

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