IDEAS home Printed from https://ideas.repec.org/a/taf/lstaxx/v53y2024i4p1402-1419.html
   My bibliography  Save this article

Projection tests for linear hypothesis in the functional response model

Author

Listed:
  • Łukasz Smaga

Abstract

This article concerns the linear hypothesis testing problem in the functional response model, which is one of the regression models considered in functional data analysis. In this model, the response is a function represented as a random process, while the predictors are random variables. To test the linear hypothesis, projection tests are constructed and theoretically justified. Namely, a kind of equivalence between the functional null hypothesis and its projected version is established. Different Gaussian processes and numbers of projections are considered in the implementation of new solutions. Moreover, as there is no one test having the best power for all correlation cases, a simple combining test is also proposed. It has satisfactory power in all cases. In simulation studies, the new tests are compared with existing methods in terms of size control and power. A real data example is also provided to illustrate the results.

Suggested Citation

  • Łukasz Smaga, 2024. "Projection tests for linear hypothesis in the functional response model," Communications in Statistics - Theory and Methods, Taylor & Francis Journals, vol. 53(4), pages 1402-1419, February.
  • Handle: RePEc:taf:lstaxx:v:53:y:2024:i:4:p:1402-1419
    DOI: 10.1080/03610926.2022.2101120
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/03610926.2022.2101120
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1080/03610926.2022.2101120?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.

    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:taf:lstaxx:v:53:y:2024:i:4:p:1402-1419. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/lsta .

    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.