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翻訳と辞書　辞書検索 [ 開発暫定版 ] スポンサード リンク Adaptive estimator ： ウィキペディア英語版 Adaptive estimator In statistics, an adaptive estimator is an estimator in a parametric or semiparametric model with nuisance parameters such that the presence of these nuisance parameters does not affect efficiency of estimation. ==Definition== Formally, let parameter ''θ'' in a parametric model consists of two parts: the parameter of interest , and the nuisance parameter . Thus . Then we will say that $\backslash scriptstyle\backslash hat\backslash nu\_n$ is an adaptive estimator of ''ν'' in the presence of ''η'' if this estimator is regular, and efficient for each of the submodels : $$ \mathcal_\nu(\eta_0) = \big\. Adaptive estimator estimates the parameter of interest equally well regardless whether the value of the nuisance parameter is known or not. The necessary condition for a regular parametric model to have an adaptive estimator is that : $$ I_(\theta) = \operatorname(z_\nu z_\eta' \, ) = 0 \quad \text\theta, where ''z''''ν'' and ''z''''η'' are components of the score function corresponding to parameters ''ν'' and ''η'' respectively, and thus ''I''''νη'' is the top-right ''k×m'' block of the Fisher information matrix ''I''(''θ''). 抄文引用元・出典: フリー百科事典『 ウィキペディア（Wikipedia）』 ■ウィキペディアで「Adaptive estimator」の詳細全文を読む スポンサード リンク 翻訳と辞書 : 翻訳のためのインターネットリソース Copyright(C) kotoba.ne.jp 1997-2016. All Rights Reserved.