Why are there differences between GPArotation::Varimax and stats::varimax?
问题 There are (at least) two different ways to varimax-rotate a loadings matrix in R, GPArotation::Varimax and stats::varimax . Oddly, even if the Kaiser-Normalization is enabled for both, they yield subtly different results. That's a bit of a pain for testing. library(GPArotation) library(psych) data("Thurstone") principal.unrotated <- principal(r = Thurstone, nfactors = 4, rotate = "none") # find unrotated PCs first loa <- unclass(principal.unrotated$loadings) varimax.stats <- stats::varimax(x