Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Library: stats
See also: draftman factor

Macro: pca
Description: PCA performs a Principal Component Analysis for x. It is possible to choose interactively between different criteria for the PCA's and confidence intervals.

Usage: pc = pca (x)
Input:
x n x p matrix
Output:
pc.y n x p matrix principal components
pc.gamma p x p matrix of eigenvectors
pc.lambda p x 1 matrix of eigenvalues

Example:
; loads the library stats
library("stats")   
; loads the library graphic
library("graphic")                                       
; reads the swiss banknote data
x  = read("bank2")             
; shows the principal components of x                          
pc = pca(x)                             
Result:
The graphic is divided into two displays. One shows a 
a scatterplot matrix of X. The second shows at the top
a parallel coordinate plot of gamma (matrix of the 
eigenvectors) and at the bottom the scree plot. 
Interactively you can choose between different criteria
for the number important principal components and 
confidence intervals for the eigenvalues (assumed that
they are really all different).

Library: stats
See also: draftman factor

Keywords - Function groups - @ A B C D E F G H I J K L M N O P Q R S T U V W X Y Z

Author: Katharina Kroel, Kerstin Zanter, 961202, Sigbert Klinke 970820
(C) MD*TECH Method and Data Technologies, 17.8.2000