Principal Component Analysis for Special Types of Data
作者： I. T. Jolliffe
DOI: 10.1007/978-1-4757-1904-8_11
关键词:
摘要: In much of statistical inference, it is assumed that a data set consists n independent observations on one or more random variables, x, and this assumption often implicit when PCA done. Another which also may be made implicitly x continuous with perhaps the stronger multivariate normality if we require to make some formal inference for PCs.
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