鄭明燕2006-07-262018-06-282006-07-262018-06-282003-07-31http://ntur.lib.ntu.edu.tw//handle/246246/20978非參數估計的核方法已被廣泛應用於實務。區域線性迴歸有許多優 點。我們研究區域線性迴歸的二次內插法，發現如此可大幅降低變異。這在估計 多維迴歸曲面時特別有用。非參數濾波問題常見於工程及財務經濟。非參數濾波 法通常包含一些濾波參數，這些參數可以針對每一時間點區域選擇或針對一段時 間區間選擇使得表現最佳。我們提出以預測誤差選擇濾波參數，並且證明在很弱 的條件下這種適濾波法與理想濾波法表現一樣好。這些方法可應用於財務經濟的 輕變異估計。Kernel methods for nonparametric estimation have been widely used in practice. Local linear regression has many advantages. We study quadratic interpolation of local linear smoothers and show that it substantially enhances the stability. This is of particular value when estimating multivariate surfaces. Problems of nonparametric filtering arise frequently in engineering and financial economics. Nonparametric filters often involve some filtering parameters. These parameters can be chosen to optimize performance locally at each time point or globally over a time interval. We propose to choose the filtering parameters via minimizing the prediction error and show that, under mild conditions, the adaptive filter performs nearly as well as the ideal filter. The techniques can also be applied to volatility estimation in financial economics.application/pdf118334 bytesapplication/pdfzh-TW國立臺灣大學數學系暨研究所適濾波自迴歸指數平滑法GARCH內插法區域線性迴歸降 變異法輕變異adaptive filteringautoregressionexponential smoothinginterpolationlocal linear regressionvariance reductionvolatilityreporthttp://ntur.lib.ntu.edu.tw/bitstream/246246/20978/1/912118M002001.pdf