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In statistics, biweight midcorrelation (also called bicor) is a measure of similarity between samples. It is median-based, rather than mean-based, thus is less sensitive to outliers, and can be a robust alternative to other similarity metrics, such as Pearson correlation or mutual information. ==Derivation== Here we find the biweight midcorrelation of two vectors and , with items, representing each item in the vector as and . First, we define as the median of a vector and as the median absolute deviation (MAD), then define and as, : Now we define the ''weights'' and as, : where is the identity function where, : Then we normalize so that the sum of the weights is 1: : Finally, we define biweight midcorrelation as, : 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「Biweight midcorrelation」の詳細全文を読む スポンサード リンク
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