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NONLINEAR ASYMMETRIC LEAST SQUARES ESTIMATORS  

Park, Seung-Hoe (Department of General Studies, Hankuk Aviation University)
Kim, Hae-Kyung (Department of Mathematics, Yonsei University)
Lee, Young (Department of Mathematics, Yonsei University)
Publication Information
Journal of the Korean Statistical Society / v.32, no.1, 2003 , pp. 47-64 More about this Journal
Abstract
In this paper, we consider the asymptotic properties of asymmetric least squares estimators for nonlinear regression models. This paper provides sufficient conditions for strong consistency and asymptotic normality of the proposed estimators and derives asymptotic relative efficiency of the pro-posed estimators to the regression quantile estimators. We give some examples and results of a Monte Carlo simulation to compare the asymmetric least squares estimators with the regression quantile estimators.
Keywords
Asymmetric least squares estimators; consistency; normality; efficiency;
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