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Canonical correspondence analysis : ウィキペディア英語版 | Canonical correspondence analysis In applied statistics, canonical correspondence analysis (CCA) is a multivariate constrained ordination technique that extracts major gradients among combinations of explanatory variables in a dataset. The requirements of a CCA are that the samples are random and independent and that the independent variables are consistent within the sample site and error-free.〔McGarigal, K., S. Cushman, and S. Stafford (2000). ''Multivariate Statistics for Wildlife and Ecology Research''. New York, New York, USA: Springer.〕 ==See also==
* Canonical correlation analysis (CANCOR)
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「Canonical correspondence analysis」の詳細全文を読む
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