IDEAS home Printed from https://ideas.repec.org/a/eee/stapro/v57y2002i4p387-391.html
   My bibliography  Save this article

The TP2 ordering of Kimeldorf and Sampson has the normal-agreeing property

Author

Listed:
  • Genest, Christian
  • Verret, François

Abstract

Kimeldorf and Sampson (Ann. Inst. Statist. Math. 39 (1987) 113) proposed a positive dependence ordering that extends the TP2 concept of dependence defined for bivariate distributions by Block et al. (Ann. Probab. 10 (1982) 765). It is shown here that in this ordering, the bivariate normal distributions with given means and variances are ordered by their correlation coefficient. It is also pointed out that except possibly for the Ali-Mikhail-Haq and Gumbel-Barnett families, none of the common classes of Archimedean copulas meets the TP2 condition of Kimeldorf and Sampson.

Suggested Citation

  • Genest, Christian & Verret, François, 2002. "The TP2 ordering of Kimeldorf and Sampson has the normal-agreeing property," Statistics & Probability Letters, Elsevier, vol. 57(4), pages 387-391, May.
    • Handle: RePEc:eee:stapro:v:57:y:2002:i:4:p:387-391
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0167-7152(02)00095-0
    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. Takemi Yanagimoto & Masashi Okamoto, 1969. "Partial orderings of permutations and monotonicity of a rank correlation statistic," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 21(1), pages 489-506, December.
    2. Z. Fang & H. Joe, 1992. "Further developments on some dependence orderings for continuous bivariate distributions," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 44(3), pages 501-517, September.
    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. Rinott, Yosef & Scarsini, Marco, 2006. "Total positivity order and the normal distribution," Journal of Multivariate Analysis, Elsevier, vol. 97(5), pages 1251-1261, May.
    2. Zalzadeh, Saeed & Pellerey, Franco, 2016. "A positive dependence notion based on componentwise unimodality of copulas," Statistics & Probability Letters, Elsevier, vol. 112(C), pages 51-57.

    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. Avérous, Jean & Genest, Christian & C. Kochar, Subhash, 2005. "On the dependence structure of order statistics," Journal of Multivariate Analysis, Elsevier, vol. 94(1), pages 159-171, May.
    2. Shyamal Ghosh & Prajamitra Bhuyan & Maxim Finkelstein, 2022. "On a bivariate copula for modeling negative dependence: application to New York air quality data," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 31(5), pages 1329-1353, December.
    3. Colangelo Antonio, 2006. "Some Positive Dependence Orderings involving Tail Dependence," Economics and Quantitative Methods qf0601, Department of Economics, University of Insubria.
    4. Colangelo, Antonio, 2008. "A study on LTD and RTI positive dependence orderings," Statistics & Probability Letters, Elsevier, vol. 78(14), pages 2222-2229, October.
    5. Moshe Shaked & Miguel A. Sordo & Alfonso Suárez-Llorens, 2012. "Global Dependence Stochastic Orders," Methodology and Computing in Applied Probability, Springer, vol. 14(3), pages 617-648, September.
    6. Harry Joe, 2018. "Dependence Properties of Conditional Distributions of some Copula Models," Methodology and Computing in Applied Probability, Springer, vol. 20(3), pages 975-1001, September.
    7. P. Gagliardini & C. Gourieroux, 2008. "Duration time‐series models with proportional hazard," Journal of Time Series Analysis, Wiley Blackwell, vol. 29(1), pages 74-124, January.
    8. Hu, Taizhong & Wei, Ying, 2001. "Multivariate stochastic comparisons of inspection and repair policies," Statistics & Probability Letters, Elsevier, vol. 53(3), pages 315-324, June.
    9. Juan-José Ganuza & José S. Penalva, 2005. "On Information and Competition in Private Value Auctions," Working Papers 158, Barcelona School of Economics.
    10. Dolati, Ali & Genest, Christian & Kochar, Subhash C., 2008. "On the dependence between the extreme order statistics in the proportional hazards model," Journal of Multivariate Analysis, Elsevier, vol. 99(5), pages 777-786, May.
    11. Aloysius Siow, 2015. "Testing Becker's Theory of Positive Assortative Matching," Journal of Labor Economics, University of Chicago Press, vol. 33(2), pages 409-441.
    12. Callaway, Brantly, 2021. "Bounds on distributional treatment effect parameters using panel data with an application on job displacement," Journal of Econometrics, Elsevier, vol. 222(2), pages 861-881.
    13. Denuit, Michel & Lambert, Philippe, 2005. "Constraints on concordance measures in bivariate discrete data," Journal of Multivariate Analysis, Elsevier, vol. 93(1), pages 40-57, March.
    14. Otso Massala & Ilia Tsetlin, 2015. "Search Before Trade-offs Are Known," Decision Analysis, INFORMS, vol. 12(3), pages 105-121.
    15. Gregorio Curello & Ludvig Sinander, 2019. "The preference lattice," Papers 1902.07260, arXiv.org, revised Feb 2024.
    16. Capéraà, Philippe & Fougères, Anne-Laure & Genest, Christian, 2000. "Bivariate Distributions with Given Extreme Value Attractor," Journal of Multivariate Analysis, Elsevier, vol. 72(1), pages 30-49, January.
    17. Ilia Tsetlin & Robert L. Winkler, 2007. "Decision Making with Multiattribute Performance Targets: The Impact of Changes in Performance and Target Distributions," Operations Research, INFORMS, vol. 55(2), pages 226-233, April.
    18. Satya P. DAS & Chetan CHATE, 2001. "Endogenous Distribution, Politics, and Growth," LIDAM Discussion Papers IRES 2001019, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES).
    19. DENUIT, Michel & SAILLET, Olivier, 2001. "Nonparametric Tests for Positive Quadrant Dependence," LIDAM Discussion Papers IRES 2001009, Université catholique de Louvain, Institut de Recherches Economiques et Sociales (IRES), revised 01 Apr 2001.
    20. Lin, Feng & Peng, Liang & Xie, Jiehua & Yang, Jingping, 2018. "Stochastic distortion and its transformed copula," Insurance: Mathematics and Economics, Elsevier, vol. 79(C), pages 148-166.

    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:57:y:2002:i:4:p:387-391. 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.