Use PCA in R (Principal Component Analysis)

Data = read. Table ("file", header = true)

R commands for PCA

Here are some r commands for PCA

Pcdat = princomp (data)-It does actual job and put the results to pcdat. It will use Covariance Matrix

Pcdat = princomp (data, Cor = true)-it will use correlation matrix

Summary (pcdat)-It will print standard deviation and proportion of variances for each component

Screeplot (pcdat)-It will plot screeplt

Biplot (pcdat) or biplot. princomp (pcdat, scale = 1)-it will give you biplot

Loadings (pcdat)-it will give information how much each variable contribute to each component. For Principal Components you can ignore

Loading subsection of the output from this command

Pcdat $ scores-it will plot scores of each observation for each variable

For further details about this and other R commands type

Help. Start ()

 

PCA encyclopedia address (with MATLAB example) http://baike.baidu.com/view/852194.htm#1