The strong consistency of the $L_1$-norm estimators in censored nonlinear regression models

  • Park, Seung-Hoe (Department of Gemeral Studies, Hankuk Ayiation University, Koyang 411-791) ;
  • Kim, Hae-Kyung (Department of Mathematics, Yonsei University)
  • 발행 : 1997.11.01

초록

This paper is concerned with the strong consistency of the $L_1$-norm estimators for the nonlinear regression models when dependent variables are subject to censoring, and provides the sufficient conditions which ensure the strong consistency of $L_1$-norm estimators of the censored regression models.

키워드

참고문헌

  1. Econometrica v.41 Regression Analysis when the Dependent Variable is Truncated Normal Amemiya, T.
  2. Communication in Statistics v.23 Consistency of $L_1$ Estimates in Censored Linear Regression Models Chen, X.R.;Wu, Y.
  3. Bulletin of the Korean Mathematical Society v.33 The Consistency Estimation in Nonlinear Regression Models with Noncompact Parameter Space Choi, S.H.;Kim, H.K.;Jang, S.H.
  4. Journal of Korean Statististics Society v.24 Asymtotic Properties of Nonlinear Least Absolute Deviation Estimators Kim, H.K.;Choi, S.H.
  5. Econometrica v.5 Uniform Convergence in Probability and Stochastic Equicontinuity Newey, W.K.
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  7. Journal of Econometrics v.27 Censored Regression Quantiles Powell, J.L.