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Matrix correlation

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  • J. Ramsay
  • Jos Berge
  • G. Styan

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Suggested Citation

  • J. Ramsay & Jos Berge & G. Styan, 1984. "Matrix correlation," Psychometrika, Springer;The Psychometric Society, vol. 49(3), pages 403-423, September.
  • Handle: RePEc:spr:psycho:v:49:y:1984:i:3:p:403-423
    DOI: 10.1007/BF02306029
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    References listed on IDEAS

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    1. Norman Cliff, 1966. "Orthogonal rotation to congruence," Psychometrika, Springer;The Psychometric Society, vol. 31(1), pages 33-42, March.
    2. Rao, C. Radhakrishna, 1979. "Separation theorems for singular values of matrices and their applications in multivariate analysis," Journal of Multivariate Analysis, Elsevier, vol. 9(3), pages 362-377, September.
    3. Jos Berge, 1983. "A generalization of Kristof's theorem on the trace of certain matrix products," Psychometrika, Springer;The Psychometric Society, vol. 48(4), pages 519-523, December.
    4. Bert Green, 1952. "The orthogonal approximation of an oblique structure in factor analysis," Psychometrika, Springer;The Psychometric Society, vol. 17(4), pages 429-440, December.
    5. James Lingoes & Peter Schönemann, 1974. "Alternative measures of fit for the Schönemann-carroll matrix fitting algorithm," Psychometrika, Springer;The Psychometric Society, vol. 39(4), pages 423-427, December.
    6. Elliot Cramer & W. Nicewander, 1979. "Some symmetric, invariant measures of multivariate association," Psychometrika, Springer;The Psychometric Society, vol. 44(1), pages 43-54, March.
    7. Peter Schönemann, 1966. "A generalized solution of the orthogonal procrustes problem," Psychometrika, Springer;The Psychometric Society, vol. 31(1), pages 1-10, March.
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    Citations

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    Cited by:

    1. Lazraq, Aziz & Cléroux, Robert, 2001. "Statistical Inference Concerning Several Redundancy Indices," Journal of Multivariate Analysis, Elsevier, vol. 79(1), pages 71-88, October.
    2. Michael Brusco & Renu Singh & Douglas Steinley, 2009. "Variable Neighborhood Search Heuristics for Selecting a Subset of Variables in Principal Component Analysis," Psychometrika, Springer;The Psychometric Society, vol. 74(4), pages 705-726, December.
    3. Yoshio Takane & Tadashi Shibayama, 1991. "Principal component analysis with external information on both subjects and variables," Psychometrika, Springer;The Psychometric Society, vol. 56(1), pages 97-120, March.
    4. Kentaro Hayashi & Peter Bentler, 2000. "On the relations among regular, equal unique variances, and image factor analysis models," Psychometrika, Springer;The Psychometric Society, vol. 65(1), pages 59-72, March.
    5. Cadima, Jorge & Cerdeira, J. Orestes & Minhoto, Manuel, 2004. "Computational aspects of algorithms for variable selection in the context of principal components," Computational Statistics & Data Analysis, Elsevier, vol. 47(2), pages 225-236, September.
    6. Rizzi, Alfredo & Vichi, Maurizio, 1995. "Representation, synthesis, variability and data preprocessing of a three-way data set," Computational Statistics & Data Analysis, Elsevier, vol. 19(2), pages 203-222, February.
    7. Prendergast, Luke A. & Li Wai Suen, Connie, 2011. "A new and practical influence measure for subsets of covariance matrix sample principal components with applications to high dimensional datasets," Computational Statistics & Data Analysis, Elsevier, vol. 55(1), pages 752-764, January.
    8. Brusco, Michael J., 2014. "A comparison of simulated annealing algorithms for variable selection in principal component analysis and discriminant analysis," Computational Statistics & Data Analysis, Elsevier, vol. 77(C), pages 38-53.
    9. Kazemilari, Mansooreh & Djauhari, Maman Abdurachman, 2015. "Correlation network analysis for multi-dimensional data in stocks market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 429(C), pages 62-75.

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