IDEAS home Printed from https://ideas.repec.org/a/hin/jnljam/632039.html
   My bibliography  Save this article

Integral Least-Squares Inferences for Semiparametric Models with Functional Data

Author

Listed:
  • Limian Zhao
  • Peixin Zhao

Abstract

The inferences for semiparametric models with functional data are investigated. We propose an integral least-squares technique for estimating the parametric components, and the asymptotic normality of the resulting integral least-squares estimator is studied. For the nonparametric components, a local integral least-squares estimation method is proposed, and the asymptotic normality of the resulting estimator is also established. Based on these results, the confidence intervals for the parametric component and the nonparametric component are constructed. At last, some simulation studies and a real data analysis are undertaken to assess the finite sample performance of the proposed estimation method.

Suggested Citation

  • Limian Zhao & Peixin Zhao, 2014. "Integral Least-Squares Inferences for Semiparametric Models with Functional Data," Journal of Applied Mathematics, Hindawi, vol. 2014, pages 1-8, July.
    • Handle: RePEc:hin:jnljam:632039
    DOI: 10.1155/2014/632039
    as

    Download full text from publisher

    File URL: http://downloads.hindawi.com/journals/JAM/2014/632039.pdf
    Download Restriction: no
    File URL: http://downloads.hindawi.com/journals/JAM/2014/632039.xml
    Download Restriction: no
    File URL: https://libkey.io/10.1155/2014/632039?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
    ---><---

    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:hin:jnljam:632039. 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: Mohamed Abdelhakeem (email available below). General contact details of provider: https://www.hindawi.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.