Limited number of principal components in PCA
David and Josh,
Thank you for the suggestions. I have attached a file ('q_values.txt') that
contains the values of the 'Q' variable.
David -- I am attempting an 'S' mode PCA, where the columns are actually the
cases (different stream gaging stations) and the rows are the variables (the
maximum flow at each station for a given year). I think the format you are
referring to is 'R' mode, but I was under the impression that R (the
program, not the PCA mode) could handle the analyses in either format. Am I
mistaken?
My first eigenvalue is:
unrotated_pca_q$sdev[1]^2
[1] 17.77812 Does that value seem large enough to explain the reduction in principal components from 65 to 54? Also, the loadings on the first PC are not particularly high: > max(abs(unrotated_pca_q$rotation[1:84])) [1] 0.1794776 Does that suggest that maybe the data are not very highly correlated? Thank you both very much for your help. Billy http://r.789695.n4.nabble.com/file/n3719440/q_values.txt q_values.txt -- View this message in context: http://r.789695.n4.nabble.com/Limited-number-of-principal-components-in-PCA-tp3704956p3719440.html Sent from the R help mailing list archive at Nabble.com.