Asymmetric Least Squares Estimation for A Nonlinear Time Series Regression Model

  • Kim, Tae Soo (Research Professor, Department of Industrial Engineering, Hanyang University, Ansan 425-791) ;
  • Kim, Hae Kyoung (Professor, Department of Mathematics, Yonsei University, Seoul, 120-791) ;
  • Yoon, Jin Hee (Ph.D, Course Student, Department of Mathematics, Yonsei University, Seoul, 120-791)
  • Published : 2001.12.01


The least squares method is usually applied when estimating the parameters in the regression models. However the least square estimator is not very efficient when the distribution of the error is skewed. In this paper, we propose the asymmetric least square estimator for a particular nonlinear time series regression model, and give the simple and practical sufficient conditions for the strong consistency of the estimators.



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