AIMS Mathematics, 2018, 3(1): 253-262. doi: 10.3934/Math.2018.1.253.

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A SOR-like AVM for the maximal correlation problem

School of mathematics, Zunyi Normal College, Zunyi, Guizhou, 563006, P. R. China

In this paper, a SOR-like alternating variable method for computing the global solution of the maximal correlation problem is presented. The monotone convergence of the SOR-like alternating variable method is proved. Numerical experiments show the effciency of our method.
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Keywords multivariate statistics; maximal correlation problem convergence; multivariateeigenvalue problem; global maximizer; power method

Citation: Jun He. A SOR-like AVM for the maximal correlation problem. AIMS Mathematics, 2018, 3(1): 253-262. doi: 10.3934/Math.2018.1.253

References

  • 1. H. Hotelling, The most predictable criterion, J. Educ. Pyschol., 26 (1935), 139–142.
  • 2. H. Hotelling, Relations between two sets of variates, Biometrika, 28 (1936), 321–377.
  • 3. M. T. Chu, J. L. Watterson, On a multivariate eigenvalue problem, part I: Algebraic theory and a power method, SIAM J. Sci. Comput., 14 (1993), 1089–1106.
  • 4. M. Hanafi, J. M. F. Ten Berge, Global optimality of the successive Maxbet algorithm, Psychometrika, 68 (2003), 97–103.
  • 5. P. Horst, Relations among m sets of measures, Psychometrika, 26 (1961), 129–149.
  • 6. J. Nocedal, S. J. Wright, Numerical Optimization, 2nd edn. Springer, New York, 2006.
  • 7. L. H. Zhang, M. T. Chu, Computing absolute maximum correlation, IMA J. Numer. Anal., 32 (2012), 163–184.
  • 8. L. H. Zhang, L. Z. Liao, L. M. Sun, Towards the global solution of the maximal correlation problem, J. Global Optim., 49 (2011), 91–107.
  • 9. L. H. Zhang, L. Z. Liao, (2012) An alternating variable method for the maximal correlation problem, J. Global Optim., 54 (2012), 199–218.

 

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