On Wednesday 30 of June 2010 23:02:09 afso...@unisinos.br wrote: > Hi all, > > I am using the vegan package to run a prcincipal components analysis > on forest structural variables (tree density, basal area, average > height, regeneration density) in R. > > However, I could not find out how to extract factor loadings > (correlations of each variable with each pca axis), as is straightforwar > in princomp. > > Do anyone know how to do that? > > Moreover, do anyone knows a function r package that produces > rotated-pca and biplots? Most packages I found did only one of these > tasks (princomp, psych, vegan). > > Thanks a lot, > Alexandre
Hi Alexandre. I haven't used the vegan package. But using princomp() and/or prcomp() is really easy. Easy is also the extraction of the loadings. Just check the structure of the result of princomp() to find the "loadings" or the result of prcomp() to find the "rotation" ( which is the same as the loadings in princomp() ). For plotting you might want to have a look at the plotpc R package. It's something I really like (and have customised it a lot to suit my needs of plotting bivariate rotated axes (=the principal components) of a given data set using the prcomp R function and even more). Don't know though if this is what you are looking for. ( ...my custom version however is not ready for a generic use. It would take to somebody to spend more time on it to remove hardcoded stuff and figure out smart automatic ways to handle co-plotting scaled and non-scaled axes (as a result of scaled=standardised and non-scaled=unstandardised PCA) on the same plot.) Also interesting is the smoothScatter functions that "produces a smoothed color density representation of the scatterplot, obtained through a kernel density estimate." It used "densCols" to "produce a vector containing colors which encode the local densities at each point in a scatterplot." Very interesting if the data-matrix to be transformed is large. Nikos ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
