IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v50y1994i2p238-264.html
   My bibliography  Save this article

The Asymptotic Distribution of Singular-Values with Applications to Canonical Correlations and Correspondence Analysis

Author

Listed:
  • Eaton, M. L.
  • Tyler, D.

Abstract

Let Xn, n = 1, 2, ... be a sequence of p - q random matrices, p >= q. Assume that for a fixed p - q matrix B and a sequence of constants bn --> [infinity], the random matrix bn(Xn - B) converges in distribution to Z. Let [psi](Xn) denote the q-vector of singular values of Xn. Under these assumptions, the limiting distribution of bn ([psi](Xn) - [psi](B)) is characterized as a function of B and of the limit matrix Z. Applications to canonical correlations and to correspondence analysis are given.

Suggested Citation

  • Eaton, M. L. & Tyler, D., 1994. "The Asymptotic Distribution of Singular-Values with Applications to Canonical Correlations and Correspondence Analysis," Journal of Multivariate Analysis, Elsevier, vol. 50(2), pages 238-264, August.
  • Handle: RePEc:eee:jmvana:v:50:y:1994:i:2:p:238-264
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(84)71041-4
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. An, Baiguo & Guo, Jianhua & Wang, Hansheng, 2013. "Multivariate regression shrinkage and selection by canonical correlation analysis," Computational Statistics & Data Analysis, Elsevier, vol. 62(C), pages 93-107.
    2. F. Chiaromonte, 1998. "On Multivariate Structures and Exhaustive Reductions," Working Papers ir98080, International Institute for Applied Systems Analysis.
    3. Bai, Z. D. & He, Xuming, 2004. "A chi-square test for dimensionality with non-Gaussian data," Journal of Multivariate Analysis, Elsevier, vol. 88(1), pages 109-117, January.
    4. Dümbgen, Lutz, 1995. "A simple proof and refinement of Wielandt's eigenvalue inequality," Statistics & Probability Letters, Elsevier, vol. 25(2), pages 113-115, November.
    5. Bura, Efstathia & Cook, R. Dennis, 2003. "Rank estimation in reduced-rank regression," Journal of Multivariate Analysis, Elsevier, vol. 87(1), pages 159-176, October.
    6. Boik, Robert J., 1998. "A Local Parameterization of Orthogonal and Semi-Orthogonal Matrices with Applications," Journal of Multivariate Analysis, Elsevier, vol. 67(2), pages 244-276, November.
    7. Fan, Jianqing & Fan, Yingying & Lv, Jinchi, 2008. "High dimensional covariance matrix estimation using a factor model," Journal of Econometrics, Elsevier, vol. 147(1), pages 186-197, November.
    8. Marcos Rangel & Duncan Thomas, 2019. "Decision-Making in Complex Households," NBER Working Papers 26511, National Bureau of Economic Research, Inc.
    9. Taskinen, Sara & Croux, Christophe & Kankainen, Annaliisa & Ollila, Esa & Oja, Hannu, 2006. "Influence functions and efficiencies of the canonical correlation and vector estimates based on scatter and shape matrices," Journal of Multivariate Analysis, Elsevier, vol. 97(2), pages 359-384, February.
    10. Yoon, Jangsu, 2024. "Identification and estimation of sequential games of incomplete information with multiple equilibria," Journal of Econometrics, Elsevier, vol. 238(2).
    11. Kuriki, Satoshi, 2005. "Asymptotic distribution of inequality-restricted canonical correlation with application to tests for independence in ordered contingency tables," Journal of Multivariate Analysis, Elsevier, vol. 94(2), pages 420-449, June.
    12. Charles Lindsey & Simon Sheather & Joseph McKean, 2014. "Using sliced mean variance–covariance inverse regression for classification and dimension reduction," Computational Statistics, Springer, vol. 29(3), pages 769-798, June.
    13. Ogasawara, Haruhiko, 2007. "Asymptotic expansions of the distributions of estimators in canonical correlation analysis under nonnormality," Journal of Multivariate Analysis, Elsevier, vol. 98(9), pages 1726-1750, October.
    14. Thomas, Duncan & Rangel, Marcos, 2020. "Decision-Making in Complex Households," CEPR Discussion Papers 14278, C.E.P.R. Discussion Papers.
    15. Haruhiko Ogasawara, 2009. "Asymptotic expansions in the singular value decomposition for cross covariance and correlation under nonnormality," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 61(4), pages 995-1017, December.
    16. F. Chiaromonte, 1997. "A Reduction Paradigm for Multivariate Laws," Working Papers ir97015, International Institute for Applied Systems Analysis.
    17. Yin, Xiangrong & Dennis Cook, R., 2004. "Asymptotic distribution of test statistic for the covariance dimension reduction methods in regression," Statistics & Probability Letters, Elsevier, vol. 68(4), pages 421-427, July.
    18. Marcos A. Rangel & Duncan Thomas, 2019. "Decision-Making in Complex Households," Working Papers 2019-070, Human Capital and Economic Opportunity Working Group.
    19. Nordhausen, Klaus & Oja, Hannu & Tyler, David E., 2022. "Asymptotic and bootstrap tests for subspace dimension," Journal of Multivariate Analysis, Elsevier, vol. 188(C).
    20. Yamada, Tomoya, 2013. "Asymptotic properties of canonical correlation analysis for one group with additional observations," Journal of Multivariate Analysis, Elsevier, vol. 114(C), pages 389-401.
    21. Yuan, Ke-Hai & Bentler, Peter M., 2000. "Inferences on Correlation Coefficients in Some Classes of Nonnormal Distributions," Journal of Multivariate Analysis, Elsevier, vol. 72(2), pages 230-248, February.
    22. Bura, E. & Yang, J., 2011. "Dimension estimation in sufficient dimension reduction: A unifying approach," Journal of Multivariate Analysis, Elsevier, vol. 102(1), pages 130-142, January.
    23. Eliana Christou, 2020. "Robust dimension reduction using sliced inverse median regression," Statistical Papers, Springer, vol. 61(5), pages 1799-1818, October.
    24. Liu, Xuejing & Huo, Lei & Wen, Xuerong Meggie & Paige, Robert, 2017. "A link-free approach for testing common indices for three or more multi-index models," Journal of Multivariate Analysis, Elsevier, vol. 153(C), pages 236-245.
    25. Cook, R. Dennis & Yin, Xiangrong, 2002. "Asymptotic distributions for testing dimensionality in q-based pHd," Statistics & Probability Letters, Elsevier, vol. 58(3), pages 233-243, July.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jmvana:v:50:y:1994:i:2:p:238-264. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/622892/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.