Principal component analysis

Format: Co[mponent] [g[raphfile]] [number of variables]

Performs principal component analysis between a number of variables.

Example:

Enter command - co

- Principal component analysis -
Enter number of columns to analyse:  4
Input 4 columns (one on each line):
c19
c20
c21
c22
Input lower limit of contribution to variance to include
component into main table (0 for all, 1 for none):
0.05

Output:

Including largest 4 components into table
Principal component analysis
Contribution to overall variance:
Co1       Co2       Co3       Co4
0.7284    0.1586    0.0603    0.0528

Correlations between components and variables:

                Co1       Co2       Co3       Co4
C19  A         -0.6979    0.6932   -0.1751   -0.0421
C20  B         -0.9193   -0.0405    0.3085   -0.2409
C21  C         -0.9095   -0.0443    0.1250    0.3941
C22  D         -0.8617   -0.4021   -0.3001   -0.0758

Principal components are derived (there is no facility to rotate them). The contribution of each to the overall variance is output, as is the correlation matrix between them and the original variables.

All components contributing more than a certain fraction of the overall variance are incorporated into the main data table as new columns at the right-hand edge of the table. They are titled Co1, Co2, etc. If the critical fraction requested is 0 then all of the components will be so incorporated, if it is 1 then none of them will be.

The orginal variables are not normalised before the analysis (i.e. they are not altered to have unit variance). The user may do this himself if he or she wishes, otherwise variables with a large variance will produce a proportionately large contribution to the analysis.

The graphing option has nothing to do with principal components analysis and is just a way of selecting multiple columns to be output to a graph file so that they can subsequently be plotted against each other (see the relevant section in the EASIGRAF documentation).