Communications of the Korean Mathematical Society (대한수학회논문집)

Korean Mathematical Society (대한수학회)
권호 표지
DOI QR코드

DOI QR Code

THE STRONG CONSISTENCY OF THE ASYMMETRIC LEAST SQUARES ESTIMATORS IN NONLINEAR CENSORED REGRESSION MODELS

  • Published : 2003.10.01
Download PDF
⟨ Previous Next ⟩

Abstract

This paper deals with the strong consistency of the asymmetric least squares for the nonlinear censored regression models which includes dependent variables cut off midway by any of external conditions, and provide the sufficient conditions which ensure the strong consistency of proposed estimators of the censored regression models. One example is given to illustrate the application of the main result.

Keywords

References

  1. Econometrica v.41 Regression analysis when the dependent variable is truncated normal T.Amemiya https://doi.org/10.2307/1914031
  2. Journal of Econometrics v.99 Simple resampling methods for censored regression quantiles Y.Billas;S.Chen;Z.Ying https://doi.org/10.1016/S0304-4076(00)00042-7
  3. Communication in Statistics v.23 Consistency of L₁Estimates in Censored Linear Regression Models X.R.Chen;Y.Wu
  4. Bull. Korean Math. Soc. v.34 The Strong Consistency of the L₁-norm Estimators in Censored Nonlinear Regression Models S.H.Choi;H.Kim
  5. Statistica Sinica v.1 Regression Percentiles using Asymmetric Squared Error Loss B.Efron
  6. Journal of Econometrics v.25 Least Absolute Deviation Estimation for the Censored Regression Model J.L.Powell https://doi.org/10.1016/0304-4076(84)90004-6
  7. Journal of Econometric v.32 Censored regression quantiles J.L.Powell https://doi.org/10.1016/0304-4076(86)90016-3
  8. Econometrica v.55 Asymmetric least squares estimation and testing W.K.Newey;L.Powell https://doi.org/10.2307/1911031