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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 Inverse-variance weighting ： ウィキペディア英語版 Inverse-variance weighting In statistics, inverse-variance weighting is a method of aggregating two or more random variables to minimize the variance of the weighted average. Each random variable is weighted in inverse proportion to its variance. Given a sequence of independent observations with variances , the inverse-variance weighted average is given by :$\backslash hat\; =\; \backslash frac\; .$ The inverse-variance weighted average has the least variance among all weighted averages, which can be calculated as :$D^2(\backslash hat)\; =\; \backslash frac\; .$ If the variances of the measurements are all equal, then the inverse-variance weighted average becomes the simple average. Inverse-variance weighting is typically used in statistical meta-analysis to combine the results from independent measurements. ==See also== *Weighted least squares 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「Inverse-variance weighting」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.