IDEAS home Printed from https://ideas.repec.org/a/bla/istatr/v78y2010i3p383-412.html
   My bibliography  Save this article

Information Measures in Perspective

Author

Listed:
  • Nader Ebrahimi
  • Ehsan S. Soofi
  • Refik Soyer

Abstract

No abstract is available for this item.

Suggested Citation

  • Nader Ebrahimi & Ehsan S. Soofi & Refik Soyer, 2010. "Information Measures in Perspective," International Statistical Review, International Statistical Institute, vol. 78(3), pages 383-412, December.
    • Handle: RePEc:bla:istatr:v:78:y:2010:i:3:p:383-412
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a search for a similarly titled item that would be available.

    Citations

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


    Cited by:

    1. Majid Eskafi & Milad Kowsari & Ali Dastgheib & Gudmundur F. Ulfarsson & Gunnar Stefansson & Poonam Taneja & Ragnheidur I. Thorarinsdottir, 2021. "A model for port throughput forecasting using Bayesian estimation," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 23(2), pages 348-368, June.
    2. Das Ujjwal & Ebrahimi Nader, 2018. "A New Method For Covariate Selection In Cox Model," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 297-314, June.
    3. Ebrahimi, Nader & Jalali, Nima Y. & Soofi, Ehsan S., 2014. "Comparison, utility, and partition of dependence under absolutely continuous and singular distributions," Journal of Multivariate Analysis, Elsevier, vol. 131(C), pages 32-50.
    4. Nelson, David & Noorbaloochi, Siamak, 2013. "Information preserving sufficient summaries for dimension reduction," Journal of Multivariate Analysis, Elsevier, vol. 115(C), pages 347-358.
    5. Abdolsaeed Toomaj & Mahdi Doostparast, 2014. "A note on signature‐based expressions for the entropy of mixed r‐out‐of‐ n systems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 61(3), pages 202-206, April.
    6. Navarro, J. & Sunoj, S.M. & Linu, M.N., 2011. "Characterizations of bivariate models using dynamic Kullback-Leibler discrimination measures," Statistics & Probability Letters, Elsevier, vol. 81(11), pages 1594-1598, November.
    7. Borgonovo, Emanuele & Hazen, Gordon B. & Jose, Victor Richmond R. & Plischke, Elmar, 2021. "Probabilistic sensitivity measures as information value," European Journal of Operational Research, Elsevier, vol. 289(2), pages 595-610.
    8. Antonio Di Crescenzo & Suchandan Kayal & Abdolsaeed Toomaj, 2019. "A past inaccuracy measure based on the reversed relevation transform," Metrika: International Journal for Theoretical and Applied Statistics, Springer, vol. 82(5), pages 607-631, July.
    9. Ujjwal Das & Nader Ebrahimi, 2018. "A New Method For Covariate Selection In Cox Model," Statistics in Transition New Series, Polish Statistical Association, vol. 19(2), pages 297-314, June.
    10. Majid Asadi & Karthik Devarajan & Nader Ebrahimi & Ehsan Soofi & Lauren Spirko‐Burns, 2022. "Elaboration Models with Symmetric Information Divergence," International Statistical Review, International Statistical Institute, vol. 90(3), pages 499-524, December.
    11. Siqing Shan & Jihong Shi & Qi Yan, 2017. "Blog Recommendation and Management Implications in an Emergency Context: An Information Entropy Perspective," Asia-Pacific Journal of Operational Research (APJOR), World Scientific Publishing Co. Pte. Ltd., vol. 34(01), pages 1-22, February.
    12. Abdolsaeed Toomaj, 2017. "On the effect of dependency in information properties of series and parallel systems," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 26(3), pages 419-435, August.
    13. Mario Hellmich, 2018. "Component importance based on dependence measures," Mathematical Methods of Operations Research, Springer;Gesellschaft für Operations Research (GOR);Nederlands Genootschap voor Besliskunde (NGB), vol. 87(2), pages 229-250, April.
    14. Abdolsaeed Toomaj & Antonio Di Crescenzo, 2020. "Connections between Weighted Generalized Cumulative Residual Entropy and Variance," Mathematics, MDPI, vol. 8(7), pages 1-27, July.
    15. Maryam Eskandarzadeh & Antonio Di Crescenzo & Saeid Tahmasebi, 2019. "Cumulative Measure of Inaccuracy and Mutual Information in k -th Lower Record Values," Mathematics, MDPI, vol. 7(2), pages 1-19, February.

    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:bla:istatr:v:78:y:2010:i:3:p:383-412. 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: Wiley Content Delivery (email available below). General contact details of provider: https://edirc.repec.org/data/isiiinl.html .

    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.