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dc.contributor.author劉智龍en_US
dc.contributor.authorLiu, Jyh-Longen_US
dc.contributor.author李昭勝, 洪慧念en_US
dc.contributor.authorLee Jack Chao-sheng, Hung Hui-Nienen_US
dc.date.accessioned2014-12-12T02:17:11Z-
dc.date.available2014-12-12T02:17:11Z-
dc.date.issued1996en_US
dc.identifier.urihttp://140.113.39.130/cdrfb3/record/nctu/#NT850337003en_US
dc.identifier.urihttp://hdl.handle.net/11536/61729-
dc.description.abstract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.zh_TW
dc.language.isozh_TWen_US
dc.subjectAkaike 資訊準則zh_TW
dc.subject有限樣本修正zh_TW
dc.subject漸近誤差zh_TW
dc.subjectAkaike's information criterionen_US
dc.subjectfinite correctionen_US
dc.subjectasymptotic biasen_US
dc.titleAkaike 資訊準則的有限樣本修正zh_TW
dc.titleFinite Correctin of Akaike's Information Criterionen_US
dc.typeThesisen_US
dc.contributor.department統計學研究所zh_TW
Appears in Collections:Thesis