<プレプリント>
AIC for ergodic diffusion processes from discrete observations

作成者
本文言語
出版者
発行日
雑誌名
出版タイプ
アクセス権
概要 Akaike’s information criterion (AIC) is proposed for evaluating statistical models constructed by the maximum likelihood estimators under the situation where the parametric models contain the true mod...el. In order to obtain AIC, it suffices to get a log likelihood function and the maximum likelihood estimator. However, we can not generally derive AIC for discretely observed diffusion processes since the transition densities of diffusion processes do not commonly have explicit forms. This paper presents AIC type of information criterion for discretely observed ergodic diffusion processes. The information criterion is constructed by using an approximate log likelihood function and an asymptotically efficient estimator. The approximate log likelihood function is based on a result of Dacunha-Castelle and Florens-Zmirou (1986). The asymptotically efficient estimator is derived from a contrast function based on a locally Gaussian approximation.続きを見る

本文情報を非表示

2005-12 pdf 221 KB 100  

詳細

レコードID
査読有無
関連情報
主題
注記
タイプ
登録日 2009.04.22
更新日 2018.02.23