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Independent exploratory factor analysis with application to atmospheric science data

Author

Listed:
  • Steffen Unkel
  • Nickolay Trendafilov
  • Abdel Hannachi
  • Ian Jolliffe

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.

Suggested Citation

  • Steffen Unkel & Nickolay Trendafilov & Abdel Hannachi & Ian Jolliffe, 2010. "Independent exploratory factor analysis with application to atmospheric science data," Journal of Applied Statistics, Taylor & Francis Journals, vol. 37(11), pages 1847-1862.
    • Handle: RePEc:taf:japsta:v:37:y:2010:i:11:p:1847-1862
    DOI: 10.1080/02664760903166280
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    Cited by:

    1. Zhi-Sheng Ye & Jian-Guo Li & Mengru Zhang, 2014. "Application of ridge regression and factor analysis in design and production of alloy wheels," Journal of Applied Statistics, Taylor & Francis Journals, vol. 41(7), pages 1436-1452, July.

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