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 _______________________________________________ grass-user mailing list [email protected] http://lists.osgeo.org/mailman/listinfo/grass-user
