IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v105i491y2010p1202-1214.html
   My bibliography  Save this article

Bayesian Variable Selection in Structured High-Dimensional Covariate Spaces With Applications in Genomics

Author

Listed:
  • Li, Fan
  • Zhang, Nancy R.

Abstract

No abstract is available for this item.

Suggested Citation

  • Li, Fan & Zhang, Nancy R., 2010. "Bayesian Variable Selection in Structured High-Dimensional Covariate Spaces With Applications in Genomics," Journal of the American Statistical Association, American Statistical Association, vol. 105(491), pages 1202-1214.
  • Handle: RePEc:bes:jnlasa:v:105:i:491:y:2010:p:1202-1214
    as

    Download full text from publisher

    File URL: http://pubs.amstat.org/doi/abs/10.1198/jasa.2010.tm08177
    File Function: full text
    Download Restriction: Access to full text is restricted to subscribers.

    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. Elin Shaddox & Francesco C. Stingo & Christine B. Peterson & Sean Jacobson & Charmion Cruickshank-Quinn & Katerina Kechris & Russell Bowler & Marina Vannucci, 0. "A Bayesian Approach for Learning Gene Networks Underlying Disease Severity in COPD," Statistics in Biosciences, Springer;International Chinese Statistical Association, vol. 0, pages 1-27.
    2. Alberto Cassese & Michele Guindani & Philipp Antczak & Francesco Falciani & Marina Vannucci, 2015. "A Bayesian model for the identification of differentially expressed genes in Daphnia magna exposed to munition pollutants," Biometrics, The International Biometric Society, vol. 71(3), pages 803-811, September.
    3. repec:bla:biomet:v:73:y:2017:i:3:p:769-779 is not listed on IDEAS
    4. repec:bla:biomet:v:73:y:2017:i:2:p:603-614 is not listed on IDEAS
    5. Zhao, Kaifeng & Lian, Heng, 2016. "The Expectation–Maximization approach for Bayesian quantile regression," Computational Statistics & Data Analysis, Elsevier, vol. 96(C), pages 1-11.
    6. Bradley W. McEvoy & Rajesh R. Nandy & Ram C. Tiwari, 2013. "Bayesian Approach for Clinical Trial Safety Data Using an Ising Prior," Biometrics, The International Biometric Society, vol. 69(3), pages 661-672, September.
    7. Sunkyung Kim & Wei Pan & Xiaotong Shen, 2013. "Network-Based Penalized Regression With Application to Genomic Data," Biometrics, The International Biometric Society, vol. 69(3), pages 582-593, September.
    8. repec:bla:biomet:v:73:y:2017:i:2:p:615-624 is not listed on IDEAS
    9. repec:bla:biomet:v:73:y:2017:i:1:p:232-241 is not listed on IDEAS
    10. Aijun Yang & Xuejun Jiang & Lianjie Shu & Jinguan Lin, 2017. "Bayesian variable selection with sparse and correlation priors for high-dimensional data analysis," Computational Statistics, Springer, vol. 32(1), pages 127-143, March.

    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:bes:jnlasa:v:105:i:491:y:2010:p:1202-1214. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Christopher F. Baum). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.