# Variance Captured for Individual Variables in PCA

The function **varcap.m** calculates the percent
variance of each original variable in a PCA model and outputs
the results graphically and to the workspace. The figure below
shows an example of the graphical output. Here the function was
used on a 5 PC model of the NIR spectra in the **nir_data.mat**
file in the PLS_Toolbox. The PCA model was built on mean centered
spectra. The function **varcap** was called from
the command line:

>>vc = varcap(mcx,loads,lamda);

where *mcx* was the mean centered spectra, *loads*
are the loadings vectors from a PCA model and *lamda* was
the axis for plotting against, in this case the wavelength. The
output is the matrix of variance captured *vc* and the
plot below. The plot shows the cumulative amount of variance captured
for each variable, with each PC shown as a different color. It
can be seen, for instance, that the model captures almost all
of the variation in the data in the 1200-1300 nm range, but less
than half around 880 nm. The second PC (light blue) is very important
for describing variation at ~1220 nm, while the fifth PC (reddish
brown) mostly describes variance around 880 nm.

### Requirements for running varcap

- MATLAB 5.0
- No other toolboxes required

### Developed by:

Barry M. Wise

Eigenvector Research, Inc.

bmw@eigenvector.com

### Download varcap.m

To get it, simply click on varcap.m
for Mac, or varcap.m for
PC. Move the file to a folder on your MATLAB path and you're
done.

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