statsmodels.multivariate.factor_rotation.promax¶
- 
statsmodels.multivariate.factor_rotation.promax(A, k=2)[source]¶ Performs promax rotation of the matrix \(A\).
This method was not very clear to me from the literature, this implementation is as I understand it should work.
Promax rotation is performed in the following steps:
- Deterine varimax rotated patterns \(V\).
 - Construct a rotation target matrix \(|V_{ij}|^k/V_{ij}\)
 - Perform procrustes rotation towards the target to obtain T
 - Determine the patterns
 
First, varimax rotation a target matrix \(H\) is determined with orthogonal varimax rotation. Then, oblique target rotation is performed towards the target.
Parameters: - A (numpy matrix) – non rotated factors
 - k (float) – parameter, should be positive
 
References
[1] Browne (2001) - An overview of analytic rotation in exploratory factor analysis
[2] Navarra, Simoncini (2010) - A guide to emprirical orthogonal functions for climate data analysis
