IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v79y2009i10p1327-1330.html
   My bibliography  Save this article

An identity for multivariate elliptically contoured matrix distribution

Author

Listed:
  • Bodnar, Taras
  • Gupta, Arjun K.

Abstract

In this paper, we derive the Stein-Haff identity for the multivariate elliptically contoured matrix distributions. Our results generalize the results of the papers by [Stein, C., 1977. Personal communication. Unpublished notes on estimating the covariance matrix] and [Haff, L.R., 1979a. An identity for the Wishart distribution with applications. J. Multivariate Anal. 9, 531-542] for the much more general family of the matrix variate distributions. Moreover, we simplify the proof of the Stein-Haff identity given by [Kubokawa, T., Srivastava, M.S., 1999. Robust improvement in estimation of a covariance matrix in an elliptically contoured distribution. Ann. Statist. 27, 600-609] for the vector elliptically contoured matrix distribution in some important partial cases.

Suggested Citation

  • Bodnar, Taras & Gupta, Arjun K., 2009. "An identity for multivariate elliptically contoured matrix distribution," Statistics & Probability Letters, Elsevier, vol. 79(10), pages 1327-1330, May.
    • Handle: RePEc:eee:stapro:v:79:y:2009:i:10:p:1327-1330
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(09)00059-5
    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. Haff, L. R., 1979. "An identity for the Wishart distribution with applications," Journal of Multivariate Analysis, Elsevier, vol. 9(4), pages 531-544, December.
    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. Taras Bodnar & Arjun Gupta, 2013. "An exact test for a column of the covariance matrix based on a single observation," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 76(6), pages 847-855, August.

    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. Kubokawa, Tatsuya & Srivastava, Muni S., 2008. "Estimation of the precision matrix of a singular Wishart distribution and its application in high-dimensional data," Journal of Multivariate Analysis, Elsevier, vol. 99(9), pages 1906-1928, October.
    2. K. Krishnamoorthy, 1991. "Estimation of a common multivariate normal mean vector," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 43(4), pages 761-771, December.
    3. Konno, Yoshihiko, 2009. "Shrinkage estimators for large covariance matrices in multivariate real and complex normal distributions under an invariant quadratic loss," Journal of Multivariate Analysis, Elsevier, vol. 100(10), pages 2237-2253, November.
    4. Chang, Ching-Hui & Pal, Nabendu, 2008. "Testing on the common mean of several normal distributions," Computational Statistics & Data Analysis, Elsevier, vol. 53(2), pages 321-333, December.
    5. Tsukuma, Hisayuki, 2010. "Shrinkage priors for Bayesian estimation of the mean matrix in an elliptically contoured distribution," Journal of Multivariate Analysis, Elsevier, vol. 101(6), pages 1483-1492, July.
    6. Tsai, Ming-Tien & Kubokawa, Tatsuya, 2007. "Estimation of Wishart mean matrices under simple tree ordering," Journal of Multivariate Analysis, Elsevier, vol. 98(5), pages 945-959, May.
    7. Kubokawa, Tatsuya & Hyodo, Masashi & Srivastava, Muni S., 2013. "Asymptotic expansion and estimation of EPMC for linear classification rules in high dimension," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 496-515.
    8. Li, Run-Ze & Fang, Kai-Tai, 1995. "Estimation of scale matrix of elliptically contoured matrix distributions," Statistics & Probability Letters, Elsevier, vol. 24(4), pages 289-297, September.
    9. Sheena Yo & Gupta Arjun K., 2003. "Estimation of the multivariate normal covariance matrix under some restrictions," Statistics & Risk Modeling, De Gruyter, vol. 21(4/2003), pages 327-342, April.
    10. Ledoit, Olivier & Wolf, Michael, 2021. "Shrinkage estimation of large covariance matrices: Keep it simple, statistician?," Journal of Multivariate Analysis, Elsevier, vol. 186(C).
    11. Sun, Xiaoqian & Zhou, Xian, 2008. "Improved minimax estimation of the bivariate normal precision matrix under the squared loss," Statistics & Probability Letters, Elsevier, vol. 78(2), pages 127-134, February.
    12. Fourdrinier, Dominique & Strawderman, William E. & Wells, Martin T., 2003. "Robust shrinkage estimation for elliptically symmetric distributions with unknown covariance matrix," Journal of Multivariate Analysis, Elsevier, vol. 85(1), pages 24-39, April.
    13. Besson, Olivier & Vincent, François & Gendre, Xavier, 2020. "A Stein’s approach to covariance matrix estimation using regularization of Cholesky factor and log-Cholesky metric," Statistics & Probability Letters, Elsevier, vol. 167(C).
    14. Perron, François, 1997. "On a Conjecture of Krishnamoorthy and Gupta, ," Journal of Multivariate Analysis, Elsevier, vol. 62(1), pages 110-120, July.
    15. Tu, Jun & Zhou, Guofu, 2011. "Markowitz meets Talmud: A combination of sophisticated and naive diversification strategies," Journal of Financial Economics, Elsevier, vol. 99(1), pages 204-215, January.
    16. Kubokawa, T. & Srivastava, M. S., 2001. "Robust Improvement in Estimation of a Mean Matrix in an Elliptically Contoured Distribution," Journal of Multivariate Analysis, Elsevier, vol. 76(1), pages 138-152, January.
    17. Shutoh, Nobumichi & Hyodo, Masashi & Seo, Takashi, 2011. "An asymptotic approximation for EPMC in linear discriminant analysis based on two-step monotone missing samples," Journal of Multivariate Analysis, Elsevier, vol. 102(2), pages 252-263, February.
    18. DeMiguel, Victor & Martin-Utrera, Alberto & Nogales, Francisco J., 2013. "Size matters: Optimal calibration of shrinkage estimators for portfolio selection," Journal of Banking & Finance, Elsevier, vol. 37(8), pages 3018-3034.
    19. Ikeda, Yuki & Kubokawa, Tatsuya, 2016. "Linear shrinkage estimation of large covariance matrices using factor models," Journal of Multivariate Analysis, Elsevier, vol. 152(C), pages 61-81.
    20. Haddouche, Anis M. & Fourdrinier, Dominique & Mezoued, Fatiha, 2021. "Scale matrix estimation of an elliptically symmetric distribution in high and low dimensions," Journal of Multivariate Analysis, Elsevier, vol. 181(C).

    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:stapro:v:79:y:2009:i:10:p:1327-1330. 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.