[GRASS-user] Calculating eigen values and % variance explained after PCA analysis

[Nikos Alexandris]

Wesley:
> Dear Colleagues,
> 
> I have run a PCA on a five band data set consisting of three optical
> bands, a canopy height model and lidar intensity measures. Output from
> the i.pca module only provides the eigen vectors. I would like to
> calculate the eigen values and % variance explained by each component
> in my PCA analysis.
> 
> Is it possible to calculate the eigen values and % variance explained
> using GRASS or should I use something like R?
> 
> I am using version 6.3 on ubuntu hardy heron.
> 
> Many thanks for your help.
> Wesley


Wesley, some relevant posts of mine (...although you have probably seen
them):

( in grass-user mailing list )

[1] # In these posts I didn't know much about PCA #
http://n2.nabble.com/i.pca--vs.--r.covar-m.eigensystem-r.mapcalc-td1885820.html#a1885821

[2] http://n2.nabble.com/Comparison-between-"i.pca"-and-R's-"prcomp()"%
3A-explanations-and-questions-td2283997.html#a2284070


( in grass-trac )

[3] http://trac.osgeo.org/grass/ticket/341

[4] http://trac.osgeo.org/grass/ticket/430


There is still m.eigensystem with which one can manually build Principal
Components and get all values. But I am not sure how to compile it
(anymore) and its more time-expensive than just load the data in R and
within a second perform PCA.

Kind regards, Nikos