Matrix rotations

Orthogonal and oblique matrix rotations.

p = number of variables, m = number of factors.

Method Parameters Purpose
Varimax   Orthogonal only. A computational faster equivalent to CF-Varimax.
Promax power 0 ... 4 Oblique only.
Crawford-Ferguson kappa 0 ... 1 Smaller kappa minimizes variables complexity and larger kappa minimizes factor complexity.
CF-Varimax Crawford-Ferguson kappa = 1/p. Spread variances across factors. Each factor tends to have either large or small loadings on a particular variable making it easy to identify each variable with a single factor.
CF-Quartimax Crawford-Ferguson kappa = 0. Minimizes variable complexity. Works well with distinct clusters without cross-loadings.
CF-Equamax Crawford-Ferguson kappa = m/(2p).  
CF-Parsimax Crawford-Ferguson kappa = (m-1) / (p+m-2).  
CF-Factor Parsimony Crawford-Ferguson kappa = 1. Minimizes factor complexity. Primarily of theoretical interest.
Oblimin gamma 0 ... 1  
O-Quartimin Oblimin gamma = 0. Equivalent to quartimax.
O-Biquartimin Oblimin gamma = 0.5.  
O-Covarimin Oblimin gamma = 1. Equivalent to varimax.
Geomin delta > 0 Minimizes variable complexity.
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