IDEAS home Printed from https://ideas.repec.org/a/spt/stecon/v3y2014i1f3_1_3.html
   My bibliography  Save this article

Improvement of Ridge Estimator When Stochastic Restrictions Are Available in the Linear Regression Model

Author

Listed:
  • Sivarajah Arumairajan
  • Pushpakanthie Wijekoon

Abstract

In this paper we propose another ridge type estimator, namely Stochastic Restricted Ordinary Ridge Estimator (SRORE) in the multiple linear regression model when the stochastic restrictions are available in addition to the sample information and when the explanatory variables are multicollinear. Necessary and sufficient conditions for the superiority of the Stochastic Restricted Ordinary Ridge Estimator over the Mixed Estimator (ME), Ridge Estimator (RE) and Stochastic Mixed Ridge Estimator (SMRE) are obtained by using the Mean Square Error Matrix (MSEM) criterion. Finally the theoretical findings of the proposed estimator are illustrated by using a numerical example and a Monte Carlo simulation.

Suggested Citation

  • Sivarajah Arumairajan & Pushpakanthie Wijekoon, 2014. "Improvement of Ridge Estimator When Stochastic Restrictions Are Available in the Linear Regression Model," Journal of Statistical and Econometric Methods, SCIENPRESS Ltd, vol. 3(1), pages 1-3.
    • Handle: RePEc:spt:stecon:v:3:y:2014:i:1:f:3_1_3
    as

    Download full text from publisher

    File URL: http://www.scienpress.com/Upload/JSEM%2fVol%203_1_3.pdf
    Download Restriction: no
    ---><---

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Fikri Akdeniz & Mahdi Roozbeh, 2019. "Generalized difference-based weighted mixed almost unbiased ridge estimator in partially linear models," Statistical Papers, Springer, vol. 60(5), pages 1717-1739, October.

    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:spt:stecon:v:3:y:2014:i:1:f:3_1_3. 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: Eleftherios Spyromitros-Xioufis (email available below). General contact details of provider: http://www.scienpress.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.