IDEAS home Printed from https://ideas.repec.org/a/eee/jmvana/v91y2004i2p161-176.html
   My bibliography  Save this article

Canonical correlation analysis based on information theory

Author

Listed:
  • Yin, Xiangrong

Abstract

In this article, we propose a new canonical correlation method based on information theory. This method examines potential nonlinear relationships between px1 vector Y-set and qx1 vector X-set. It finds canonical coefficient vectors a and b by maximizing a more general measure, the mutual information, between aTX and bTY. We use a permutation test to determine the pairs of the new canonical correlation variates, which requires no specific distributions for X and Y as long as one can estimate the densities of aTX and bTY nonparametrically. Examples illustrating the new method are presented.

Suggested Citation

  • Yin, Xiangrong, 2004. "Canonical correlation analysis based on information theory," Journal of Multivariate Analysis, Elsevier, vol. 91(2), pages 161-176, November.
    • Handle: RePEc:eee:jmvana:v:91:y:2004:i:2:p:161-176
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0047-259X(03)00129-5
    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.

    References listed on IDEAS

    as
    1. Hinkley, D. V., 1997. "Discussion of paper by H. Li & G.S. Maddala," Journal of Econometrics, Elsevier, vol. 80(2), pages 319-323, October.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Rivas, José & Perea, José Manuel & De-Pablos-Heredero, Carmen & Angon, Elena & Barba, Cecilio & García, Antón, 2019. "Canonical correlation of technological innovation and performance in sheep's dairy farms: Selection of a set of indicators," Agricultural Systems, Elsevier, vol. 176(C).
    2. Iaci, Ross & Sriram, T.N., 2013. "Robust multivariate association and dimension reduction using density divergences," Journal of Multivariate Analysis, Elsevier, vol. 117(C), pages 281-295.
    3. Ross Iaci & T.N. Sriram & Xiangrong Yin, 2010. "Multivariate Association and Dimension Reduction: A Generalization of Canonical Correlation Analysis," Biometrics, The International Biometric Society, vol. 66(4), pages 1107-1118, December.
    4. Iaci, Ross & Yin, Xiangrong & Zhu, Lixing, 2016. "The Dual Central Subspaces in dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 145(C), pages 178-189.
    5. Majid Asadi & Somayeh Zarezadeh, 2020. "A unified approach to constructing correlation coefficients between random variables," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 83(6), pages 657-676, August.
    6. S. Yaser Samadi & L. Billard & M. R. Meshkani & A. Khodadadi, 2017. "Canonical correlation for principal components of time series," Computational Statistics, Springer, vol. 32(3), pages 1191-1212, September.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Marazzi, A., 2002. "Bootstrap tests for robust means of asymmetric distributions with unequal shapes," Computational Statistics & Data Analysis, Elsevier, vol. 39(4), pages 503-528, June.
    2. Peter C.B. Phillips, 2001. "Bootstrapping Spurious Regression," Cowles Foundation Discussion Papers 1330, Cowles Foundation for Research in Economics, Yale University.
    3. O'Gorman, Thomas W., 2001. "An adaptive permutation test procedure for several common tests of significance," Computational Statistics & Data Analysis, Elsevier, vol. 35(3), pages 335-350, January.
    4. Kim, Jae H., 1999. "Asymptotic and bootstrap prediction regions for vector autoregression," International Journal of Forecasting, Elsevier, vol. 15(4), pages 393-403, October.
    5. Baddeley, Adrian & Hardegen, Andrew & Lawrence, Thomas & Milne, Robin K. & Nair, Gopalan & Rakshit, Suman, 2017. "On two-stage Monte Carlo tests of composite hypotheses," Computational Statistics & Data Analysis, Elsevier, vol. 114(C), pages 75-87.
    6. Xue, Yuan & Zhang, Nan & Yin, Xiangrong & Zheng, Haitao, 2017. "Sufficient dimension reduction using Hilbert–Schmidt independence criterion," Computational Statistics & Data Analysis, Elsevier, vol. 115(C), pages 67-78.
    7. Polansky, Alan M., 2001. "Bandwidth selection for the smoothed bootstrap percentile method," Computational Statistics & Data Analysis, Elsevier, vol. 36(3), pages 333-349, May.
    8. Nur, Darfiana & Wolff, Rodney C. & Mengersen, Kerrie L., 2001. "Phase randomisation: numerical study of higher cumulants behaviour," Computational Statistics & Data Analysis, Elsevier, vol. 37(4), pages 487-513, October.
    9. Cribari-Neto, Francisco & Frery, Alejandro C. & Silva, Michel F., 2002. "Improved estimation of clutter properties in speckled imagery," Computational Statistics & Data Analysis, Elsevier, vol. 40(4), pages 801-824, October.
    10. Hennig, Christian & Hausdorf, Bernhard, 2004. "Distance-based parametric bootstrap tests for clustering of species ranges," Computational Statistics & Data Analysis, Elsevier, vol. 45(4), pages 875-895, May.
    11. Clements, Michael P. & Taylor, Nick, 2001. "Bootstrapping prediction intervals for autoregressive models," International Journal of Forecasting, Elsevier, vol. 17(2), pages 247-267.
    12. Dean, C. B. & Ugarte, M. D. & Militino, A. F., 2004. "Penalized quasi-likelihood with spatially correlated data," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 235-248, March.
    13. Bacci, Silvia & Bartolucci, Francesco, 2014. "Mixtures of equispaced normal distributions and their use for testing symmetry with univariate data," Computational Statistics & Data Analysis, Elsevier, vol. 71(C), pages 262-272.
    14. Groenewold, Nicolaas & Fraser, Patricia, 2001. "Tests of asset-pricing models: how important is the iid-normal assumption?," Journal of Empirical Finance, Elsevier, vol. 8(4), pages 427-449, September.
    15. Habimana, Olivier, 2016. "Asymmetric nonlinear mean reversion in real effective exchange rates: A Fisher-type panel unit root test applied to Sub-Saharan Africa," The Journal of Economic Asymmetries, Elsevier, vol. 14(PB), pages 189-198.
    16. Peng, Yingwei, 2003. "Fitting semiparametric cure models," Computational Statistics & Data Analysis, Elsevier, vol. 41(3-4), pages 481-490, January.
    17. Taylor, Nicholas, 2002. "The economic and statistical significance of spread forecasts: Evidence from the London Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 26(4), pages 795-818, April.
    18. Wisnowski, James W. & Simpson, James R. & Montgomery, Douglas C. & Runger, George C., 2003. "Resampling methods for variable selection in robust regression," Computational Statistics & Data Analysis, Elsevier, vol. 43(3), pages 341-355, July.
    19. Cribari-Neto, Francisco, 2004. "Asymptotic inference under heteroskedasticity of unknown form," Computational Statistics & Data Analysis, Elsevier, vol. 45(2), pages 215-233, March.
    20. Barras, Laurent, 2007. "International conditional asset allocation under specification uncertainty," Journal of Empirical Finance, Elsevier, vol. 14(4), pages 443-464, September.

    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:91:y:2004:i:2:p:161-176. 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.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with 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.