Journal of applied mathematics & informatics

The Korean Society for Computational and Applied Mathematics (한국전산응용수학회)
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THE CENSORED REGRESSION QUANTILE ESTIMATORS FOR NONLINEAR REGRESSION MODEL

  • Park, Seung-Hoe (Department of General Studies, Hankuk Aviation University)
  • Published : 2003.09.01

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Abstract

In this paper, we consider the asymptotic properties of regression quantile estimators for the nonlinear regression model when dependent variables are subject to censoring time, and propose the sufficient conditions which ensure consistency and asymptotic normality for regression quantile estimators in censored nonlinear regression model. Also, we drive the asymptotic relative efficiency of the censored regression model with respect to the ordinary regression model.

Keywords

References

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