IDEAS home Printed from https://ideas.repec.org/a/spr/testjl/v17y2008i3p491-492.html
   My bibliography  Save this article

Comparison of Bayesian objective procedures for variable selection in linear regression

Author

Listed:
  • Elías Moreno
  • F. Girón

Abstract

No abstract is available for this item.

Suggested Citation

  • Elías Moreno & F. Girón, 2008. "Comparison of Bayesian objective procedures for variable selection in linear regression," TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, Springer;Sociedad de Estadística e Investigación Operativa, vol. 17(3), pages 491-492, November.
  • Handle: RePEc:spr:testjl:v:17:y:2008:i:3:p:491-492
    DOI: 10.1007/s11749-008-0095-9
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s11749-008-0095-9
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s11749-008-0095-9?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    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. Dimitris Fouskakis & Ioannis Ntzoufras, 2017. "Information consistency of the Jeffreys power-expected-posterior prior in Gaussian linear models," METRON, Springer;Sapienza Università di Roma, vol. 75(3), pages 371-380, December.
    2. Sang Gil Kang & Woo Dong Lee & Yongku Kim, 2022. "Objective Bayesian group variable selection for linear model," Computational Statistics, Springer, vol. 37(3), pages 1287-1310, July.
    3. Moreno, E. & Girón, F.J. & Martínez, M.L. & Vázquez-Polo, F.J. & Negrín, M.A., 2013. "Optimal treatments in cost-effectiveness analysis in the presence of covariates: Improving patient subgroup definition," European Journal of Operational Research, Elsevier, vol. 226(1), pages 173-182.
    4. Minerva Mukhopadhyay & Sourabh Bhattacharya, 2022. "Bayes factor asymptotics for variable selection in the Gaussian process framework," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 74(3), pages 581-613, June.
    5. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.

    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:spr:testjl:v:17:y:2008:i:3:p:491-492. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.