具有AR(1)誤差非線性迴歸模型的廣義截斷平均數

Abstract

本計劃將介紹廣義截斷平均數及feasible 廣義截斷平均數用以處理非線性迴歸模型其誤差具有AR(1)性質的問題。我們將證明這些估計量比Welsh(1987)的截斷平均數為有效。因此我們希望藉此把線性迴歸的廣義估計觀念延伸到無母數迴歸的問題。

In this project, we will apply the idea of trimmed mean of Welsh(1987) to introduce generalized and feasible generalized trimmed means for the nonlinear regression with AR(1) error model. We also expect to show that these estimators are asymptotically more efficient than the trimmed means. These results then extend the concept of generalized and feasible generalized least squares estimators for linear regression with AR(1) error model to the robust estimators for nonlinear regression models. Monte Carlo simulation and data analysis will also be conducted.