Independent exploratory factor analysis with application to atmospheric science data

Abstract

The independent exploratory factor analysis method is introduced for recovering independent latent sources from their observed mixtures. The new model is viewed as a method of factor rotation in exploratory factor analysis (EFA). First, estimates for all EFA model parameters are obtained simultaneously. Then, an orthogonal rotation matrix is sought that minimizes the dependence between the common factors. The rotation of the scores is compensated by a rotation of the initial loading matrix. The proposed approach is applied to study winter monthly sea-level pressure anomalies over the Northern Hemisphere. The North Atlantic Oscillation, the North Pacific Oscillation, and the Scandinavian pattern are identified among the rotated spatial patterns with a physically interpretable structure.

Keywords:

• noisy independent component analysis
• exploratory factor analysis
• factor rotation
• more variables than observations
• rotated spatial patterns
• gridded climate data
• sea-level pressure anomalies

Acknowledgements

The authors are grateful to the two anonymous reviewers for their helpful comments on the first draft of this paper.