IDEAS home Printed from https://ideas.repec.org/a/anm/alpnmr/v7y2019i1p13-24.html
   My bibliography  Save this article

Comparison of Parametric and Non-Parametric Estimation Methods in Linear Regression Model

Author

Listed:
  • Tolga Zaman
  • Kamil Alakuş

Abstract

In this study, the aim was to review the methods of parametric and non-parametric analyses in simple linear regression model. The least squares estimator (LSE) in parametric analysis of the model, and Mood-Brown and Theil-Sen methods that estimates the parameters according to the median value in non-parametric analysis of the model are introduced. Also, various weights of Theil-Sen method are examined and estimators are discussed. In an attempt to show the need for non-parametric methods, results are evaluated based on real life data.

Suggested Citation

  • Tolga Zaman & Kamil Alakuş, 2019. "Comparison of Parametric and Non-Parametric Estimation Methods in Linear Regression Model," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 7(1), pages 13-24, June.
    • Handle: RePEc:anm:alpnmr:v:7:y:2019:i:1:p:13-24
    DOI: http://dx.doi.org/10.17093/alphanumeric.346469
    as

    Download full text from publisher

    File URL: https://www.alphanumericjournal.com/media/Issue/volume-7-issue-1-2019/comparison-of-parametric-and-non-parametric-estimation-metho_dpljZMf.pdf
    Download Restriction: no
    File URL: https://alphanumericjournal.com/article/comparison-of-parametric-and-non-parametric-estimation-methods-in-linear-regression-model/
    Download Restriction: no
    File URL: https://libkey.io/http://dx.doi.org/10.17093/alphanumeric.346469?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
    ---><---

    References listed on IDEAS

    as
    1. Tolga Zaman & Kamil Alakuş, 2016. "Some Robust Estimation Methods and Their Applications," Alphanumeric Journal, Bahadir Fatih Yildirim, vol. 3(2), pages 73-82, December.
    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.

      More about this item

      Keywords

      Least Squares; Mean Absolute Deviation; Median; Mood-Brown Estimator; Outlier; Theil-Sen Estimator;
      All these keywords.

      JEL classification:

      • C40 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - General

      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:anm:alpnmr:v:7:y:2019:i:1:p:13-24. 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: Bahadir Fatih Yildirim (email available below). General contact details of provider: https://www.alphanumericjournal.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.