IDEAS home Printed from https://ideas.repec.org/a/spr/aistmt/v62y2010i2p249-275.html
   My bibliography  Save this article

Oracle inequality for conditional density estimation and an actuarial example

Author

Listed:
  • Sam Efromovich

Abstract

No abstract is available for this item.

Suggested Citation

  • Sam Efromovich, 2010. "Oracle inequality for conditional density estimation and an actuarial example," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 62(2), pages 249-275, April.
    • Handle: RePEc:spr:aistmt:v:62:y:2010:i:2:p:249-275
    DOI: 10.1007/s10463-008-0185-1
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10463-008-0185-1
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1007/s10463-008-0185-1?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.

    References listed on IDEAS

    as
    1. Koul, Hira L. & Sakhanenko, Lyudmila, 2005. "Goodness-of-fit testing in regression: A finite sample comparison of bootstrap methodology and Khmaladze transformation," Statistics & Probability Letters, Elsevier, vol. 74(3), pages 290-302, October.
    Full references (including those not matched with items on IDEAS)

    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. Jiwoong Kim, 2020. "Implementation of a goodness-of-fit test through Khmaladze martingale transformation," Computational Statistics, Springer, vol. 35(4), pages 1993-2017, December.
    2. Juan Mora & Alicia Pérez-Alonso, 2009. "Specification tests for the distribution of errors in nonparametric regression: a martingale approach," Journal of Nonparametric Statistics, Taylor & Francis Journals, vol. 21(4), pages 441-452.
    3. Thomas Parker, 2010. "A comparison of alternative approaches to sup-norm goodness of fit tests with estimated parameters," CeMMAP working papers CWP34/10, Centre for Microdata Methods and Practice, Institute for Fiscal Studies.
    4. Feng, Huijun & Peng, Liang, 2012. "Jackknife empirical likelihood tests for error distributions in regression models," Journal of Multivariate Analysis, Elsevier, vol. 112(C), pages 63-75.

    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:aistmt:v:62:y:2010:i:2:p:249-275. 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: 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.