透過您的圖書館登入
IP:3.16.181.239
  • 期刊

The Local Linear M-Estimator with a Robust Initial Estimate

並列摘要


In the field of nonparametric regression, the local linear M-estimator (LLM; Fan and Jiang 1999) is proposed to adjust for the unrobustness of the local linear estimator (LLE; Fan 1992, 1993). In practice, the LLM is often computed using Newton method together with an initial estimate produced by the LLE. However, by the unrobustness of the LLE, such initial estimate might be far from the global minimizer of M function. In this case, the Newton method might provide an incorrect solution for the LLM. To improve the drawback, a robust initial estimate for Newton method is proposed. Simulation results show that our robust initial estimate is useful when using Newton method to find a solution for the LLM.

參考文獻


Besl, P.J.,Birch, J.B.,Watson, L.T.(1989).Robust window operators.Machine Vision and Applications.2,179-191.
Cleveland, W.S.(1979).Robust locally weighted regression and smoothing scatterplots.Journal of the American Statistical Association.74,829-836.
Donoho, D.L.,Johnstone, I.M.(1994).Ideal spatial adaptation by wavelet shrinkage.Biometrika.81,425-455.
Eubank, R.L.(1988).Spline Smoothing and Nonparametric Regression.New York:Marcel Dekker.
Fan, J.(1992).Design-adaptive nonparametric regression.Journal of the American Statistical Association.87,998-1004.

延伸閱讀