[R] Principal Component Analysis explained variance

Hi there, How can I know the explaned variance of a PC axis generated by prcomp()? Kind regards, miltinho Brazil __ [[alternative HTML version deleted]] __ R-help@stat.math.ethz.ch mailing

Re: [R] Principal Component Analysis explained variance

Milton Cezar Ribeiro wrote: Hi there, How can I know the explaned variance of a PC axis generated by prcomp()? From the standard deviations of each component, you could do something like this maybe: prcomp(USArrests, scale = TRUE)$sdev^2 / ncol(USArrests) [1] 0.62006039 0.24744129

[R] principal component analysis in affy

Hi, I have been using the prcomp function to perform PCA on my example microarray data, (stored in metric text files) which looks like this: 1a 1b 1c 1d 1e 1f ...4r 4s 4t g11.2705 1.2766

Re: [R] principal component analysis in affy

1) Please learn to wrap your emails to 72 characters per line. See http://expita.com/nomime.html 2) You might have better luck with the BioConductor folks. Their mailing list is https://stat.ethz.ch/mailman/listinfo/bioconductor 3) The affy package has many functions including some algorithms

[R] principal component analysis

Hello, I have used prcomp and the variances for the first 3 PC's are 2.65, 1.97 and 0.38. When I plot the principal component values for each data point I can see that the points lie in a plane as one might expect from the variances. But this plane is diagonal through the 3D space of the first