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Newton Algorithms for Analytic Rotation: an Implicit Function Approach

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  • Robert Boik

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Suggested Citation

  • Robert Boik, 2008. "Newton Algorithms for Analytic Rotation: an Implicit Function Approach," Psychometrika, Springer;The Psychometric Society, vol. 73(2), pages 231-259, June.
  • Handle: RePEc:spr:psycho:v:73:y:2008:i:2:p:231-259 DOI: 10.1007/s11336-007-9027-y
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    References listed on IDEAS

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    1. P. Bentler, 1977. "Factor simplicity index and transformations," Psychometrika, Springer;The Psychometric Society, vol. 42(2), pages 277-295, June.
    2. Robert Jennrich, 2004. "Rotation to simple loadings using component loss functions: The orthogonal case," Psychometrika, Springer;The Psychometric Society, pages 257-273.
    3. Robert Jennrich, 2002. "A simple general method for oblique rotation," Psychometrika, Springer;The Psychometric Society, pages 7-19.
    4. Douglas Clarkson & Robert Jennrich, 1988. "Quartic rotation criteria and algorithms," Psychometrika, Springer;The Psychometric Society, pages 251-259.
    5. Robert Jennrich, 1973. "Standard errors for obliquely rotated factor loadings," Psychometrika, Springer;The Psychometric Society, vol. 38(4), pages 593-604, December.
    6. Claude Archer & Robert Jennrich, 1973. "Standard errors for rotated factor loadings," Psychometrika, Springer;The Psychometric Society, pages 581-592.
    7. repec:ucp:bkecon:9780226316529 is not listed on IDEAS
    8. Robert J. Boik, 2003. "Principal component models for correlation matrices," Biometrika, Biometrika Trust, vol. 90(3), pages 679-701, September.
    9. Magnus, J.R. & Neudecker, H., 1979. "The commutation matrix : Some properties and applications," Other publications TiSEM d0b1e779-7795-4676-ac98-1, Tilburg University, School of Economics and Management.
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    Cited by:

    1. Boik, Robert J., 2013. "Model-based principal components of correlation matrices," Journal of Multivariate Analysis, Elsevier, vol. 116(C), pages 310-331.
    2. Magnus, Jan R., 2010. "On the concept of matrix derivative," Journal of Multivariate Analysis, Elsevier, vol. 101(9), pages 2200-2206, October.

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