This part of the comment wasn’t about PCA/FA, hence “without the PCA”. The formal name for what I had in mind is ICA, which often works by maximizing kurtosis.
What you seemed to be saying is that a certain rotation (“one should rotate them so that the resulting axes have a sparse relationship with the original cases”) has “actually been used” and “it basically assumes that causality flows from variables with higher kurtosis to variables with lower kurtosis”.
I don’t see what the kurtosis-maximizing algorithm has to do with the choice of rotation used in factor analysis or PCA.
This part of the comment wasn’t about PCA/FA, hence “without the PCA”. The formal name for what I had in mind is ICA, which often works by maximizing kurtosis.
What you seemed to be saying is that a certain rotation (“one should rotate them so that the resulting axes have a sparse relationship with the original cases”) has “actually been used” and “it basically assumes that causality flows from variables with higher kurtosis to variables with lower kurtosis”.
I don’t see what the kurtosis-maximizing algorithm has to do with the choice of rotation used in factor analysis or PCA.