二、主成分和因子分析

主成分：
http://setosa.io/ev/
http://setosa.io/ev/principal-component-analysis/
http://journal.frontiersin.org/article/10.3389/fgene.2013.00127/full
http://www.sthda.com/english/wiki/principal-component-analysis-the-basics-you-should-read-r-software-and-data-mining
http://www.stata.com/features/overview/principal-components/

因子分析：
http://web.stanford.edu/class/psych253/tutorials/FactorAnalysis.html
http://www.uni-kiel.de/psychologie/rexrepos/posts/multFA.html
http://www.sthda.com/english/wiki/correspondence-analysis-in-r-the-ultimate-guide-for-the-analysis-the-visualization-and-the-interpretation-r-software-and-data-mining

https://www.princeton.edu/~otorres/Factor.pdf
http://rtutorialseries.blogspot.com/2011/10/r-tutorial-series-exploratory-factor.html

比较
http://stats.stackexchange.com/questions/95038/how-does-factor-analysis-explain-the-covariance-while-pca-explains-the-variance