Confidence Intervals for the Number of Components in Factor Analysis and Principal Components Analysis via Subsampling
通过子抽样构造因子分析与主成分分析的成分数量置信区间
Factor analysis (FA) and principal component analysis (PCA) are popular statistical methods for summarizing and explaining the variability in multivariate datasets. By default, FA and PCA assume the number of components or factors to be known \emph{a priori}. However, in practice the users first estimate the number of factors or components and then perform FA and PCA analyses using the point estimate. Therefore, in practice the users ignore any uncertainty in the point…