Please could someone point me in the right direction as I appear to be having a total mental block with fairly basic PCA problem!
I have a large dataframe where rows represent independent observations and columns are variables. I am wanting to perform PCA sequentially on blocks of nrows at a time and produce a graphical output of the loadings for the first 2 EOFs for each variable.
I'm sure I've performed a very similar routine in the past, but the method is currently escaping me.
Any help gratefully received!
Hi Laura,
data(iris) iris.dat <- iris[,1:4] pca.1 <- prcomp(iris.dat[1:50, ], scale = TRUE) pca.2 <- prcomp(iris.dat[51:100, ], scale = TRUE) pca.3 <- prcomp(iris.dat[100:150, ], scale = TRUE)
biplot(pca.1) etc...
There is a better way of subsetting this data set as the 5th col of iris is a factor and we could use the subset argument to prcomp to do the subsetting without having to know that there are 50 rows per species. Take a look at that argument if you have a variable that defines the blocks for you.
Is this what you were after?
All the best,
Gav -- %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~% Gavin Simpson [T] +44 (0)20 7679 5522 ENSIS Research Fellow [F] +44 (0)20 7679 7565 ENSIS Ltd. & ECRC [E] gavin.simpsonATNOSPAMucl.ac.uk UCL Department of Geography [W] http://www.ucl.ac.uk/~ucfagls/cv/ 26 Bedford Way [W] http://www.ucl.ac.uk/~ucfagls/ London. WC1H 0AP. %~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%~%
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