標題: 在無參數混合效應模型中進行由資料驅使的碎形波收縮
Data-Driven Wavlet Shrinkage for Nonparametric Mixed-effects Models
作者: 張慧雲
Huei-yun Chang
盧鴻興
Henry Horng-Shing Lu
統計學研究所
關鍵字: 無參數混合效應模型;碎形波收縮;無參數迴歸;最佳線性不偏預測;交叉確認法;廣義交叉確認法;Nonparametric Mixed-effects Models;Wavelet Shrinkage;Nonparametric Regression;best linear unbiased prediction(BLUP);cross-validation method;generalized cross-validation method
公開日期: 1998
摘要: 這篇論文利用觀察到的資料來選擇在無參數混合效應模型中的碎型波收縮的參數,方法包括交叉確認法(cross-validation method)與廣義的交叉確認法(generalized cross-validation)兩類方法.經由模擬研究,我們發現,特別是在樣本數較小及誤差程度不知道時,廣義的交叉確認法是較有效的,較可靠的,及較快的方法.
This study investigates the data-driven selection method of the threshold parameter in the wavelet shrinkage method for nonparametric mixed-effects models. The cross-validation and generalized cross-validation methods are studied. Through the simulation studies, the generalized cross-validation method turns out to be a efficient, reliable, and fast method in varticular when sample sizes are small and the noise levels are unknown.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT870337001
http://hdl.handle.net/11536/63989
Appears in Collections:Thesis