IDEAS home Printed from https://ideas.repec.org/a/ids/injdan/v12y2020i4p318-334.html
   My bibliography  Save this article

Inference in mixed linear models with four variance components - Sub-D and Sub-DI

Author

Listed:
  • Adilson Da Silva
  • António Monteiro
  • Miguel Fonseca

Abstract

This work approaches the new estimators for variance components in mixed linear models Sub-D and its improved version Sub-DI, developed and tested by Silva (2017). Both estimators were deduced and tested in mixed linear models with two and three variance components; the authors gave the corresponding formulations in models with an arbitrary number of variance components but no one had ever tested their performances in models with more than three variance components. Particularly, here we aim to give the explicit formulations for both Sub-D and Sub-DI in models with four variance components, as well as a numerical example testing their performances. Tables containing the results of the numerical example will be given.

Suggested Citation

  • Adilson Da Silva & António Monteiro & Miguel Fonseca, 2020. "Inference in mixed linear models with four variance components - Sub-D and Sub-DI," International Journal of Data Analysis Techniques and Strategies, Inderscience Enterprises Ltd, vol. 12(4), pages 318-334.
  • Handle: RePEc:ids:injdan:v:12:y:2020:i:4:p:318-334
    as

    Download full text from publisher

    File URL: http://www.inderscience.com/link.php?id=111482
    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.

    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:ids:injdan:v:12:y:2020:i:4:p:318-334. 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: Sarah Parker (email available below). General contact details of provider: http://www.inderscience.com/browse/index.php?journalID=282 .

    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.