IDEAS home Printed from https://ideas.repec.org/a/bes/jnlasa/v98y2003p352-368.html
   My bibliography  Save this article

Generalized Nonlinear Modeling With Multivariate Free-Knot Regression Splines

Author

Listed:
  • Holmes C.C.
  • Mallick B.K.

Abstract

No abstract is available for this item.

Suggested Citation

  • Holmes C.C. & Mallick B.K., 2003. "Generalized Nonlinear Modeling With Multivariate Free-Knot Regression Splines," Journal of the American Statistical Association, American Statistical Association, vol. 98, pages 352-368, January.
    • Handle: RePEc:bes:jnlasa:v:98:y:2003:p:352-368
    as

    Download full text from publisher

    File URL: http://www.ingentaconnect.com/content/asa/jasa/2003/00000098/00000462/art00008
    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. Wai-Yin Poon & Hai-Bin Wang, 2014. "Multivariate partially linear single-index models: Bayesian analysis," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 26(4), pages 755-768, December.
    2. Duchwan Ryu & Devrim Bilgili & Önder Ergönül & Faming Liang & Nader Ebrahimi, 2018. "A Bayesian Generalized Linear Model for Crimean–Congo Hemorrhagic Fever Incidents," Journal of Agricultural, Biological and Environmental Statistics, Springer;The International Biometric Society;American Statistical Association, vol. 23(1), pages 153-170, March.
    3. Pena, Daniel & Redondas, Dolores, 2006. "Bayesian curve estimation by model averaging," Computational Statistics & Data Analysis, Elsevier, vol. 50(3), pages 688-709, February.
    4. Mary Meyer & Amber Hackstadt & Jennifer Hoeting, 2011. "Bayesian estimation and inference for generalised partial linear models using shape-restricted splines," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 23(4), pages 867-884.

    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:98:y:2003:p:352-368. 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: Christopher F. Baum (email available below). General contact details of provider: http://www.amstat.org/publications/jasa/index.cfm?fuseaction=main .

    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.