標題: Akaike 資訊準則的有限樣本修正
Finite Correctin of Akaike's Information Criterion
作者: 劉智龍
Liu, Jyh-Long
李昭勝, 洪慧念
Lee Jack Chao-sheng, Hung Hui-Nien
統計學研究所
關鍵字: Akaike 資訊準則;有限樣本修正;漸近誤差;Akaike's information criterion;finite correction;asymptotic bias
公開日期: 1996
摘要: 在這篇論文裡,我們考慮 Akaike 資訊準則的有限樣本修正。我們 把最大概似函數的 漸近誤差計算到o(1/n)的收斂速度用來做 Akaike 資 訊準則的有限樣本修正。另外我們也 導出了收斂速度為o(1/n)的最大概 似估計量的漸近誤差。 In this paper we consider the finite correction of Akaike's information crit erion and refine it by considering the asymptotic bias of the maximumlikelihoo d with the rate of convergence is o(1/n). The asymptotic bias of the ML estima tors whose rate of convergenceis o(1/n) are also derived.
URI: http://140.113.39.130/cdrfb3/record/nctu/#NT850337003
http://hdl.handle.net/11536/61729
Appears in Collections:Thesis