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

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ZAMAN T., ALAKUŞ K.

Alphanumeric Journal, vol.7, no.1, pp.13-24, 2019 (Peer-Reviewed Journal) identifier

  • Publication Type: Article / Article
  • Volume: 7 Issue: 1
  • Publication Date: 2019
  • Doi Number: 10.17093/alphanumeric.346469
  • Journal Name: Alphanumeric Journal
  • Journal Indexes: TR DİZİN (ULAKBİM)
  • Page Numbers: pp.13-24
  • Ondokuz Mayıs University Affiliated: Yes

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 estimatesthe parameters according to the median value in non-parametric analysis of the model are introduced. Also, various weights ofTheil-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.