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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 Anscombe transform ： ウィキペディア英語版 Anscombe transform In statistics, the Anscombe transform, named after Francis Anscombe, is a variance-stabilizing transformation that transforms a random variable with a Poisson distribution into one with an approximately standard Gaussian distribution. The Anscombe transform is widely used in photon-limited imaging (astronomy, X-ray) where images naturally follow the Poisson law. The Anscombe transform is usually used to pre-process the data in order to make the standard deviation approximately constant. Then denoising algorithms designed for the framework of additive white Gaussian noise are used; the final estimate is then obtained by applying an inverse Anscombe transformation to the denoised data. ==Definition== For the Poisson distribution the mean $m$ and variance $v$ are not independent: $m\; =\; v$. The Anscombe transform〔 〕 : $A:x\; \backslash mapsto\; 2\backslash sqrt\}\; \backslash ,$ aims at transforming the data so that the variance is set approximately 1 whatever the mean. It transforms Poissonian data $x$ (with mean $m$) to approximately Gaussian data of mean $2\backslash sqrt\; -\; 1/(4\backslash sqrt)$ and standard deviation 1. This approximation is valid provided that $m$ is larger than 4. 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「Anscombe transform」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.