Comparison of Parametric and Non-Parametric Estimation Methods in Linear Regression Model
Alphanumeric Journal, vol.7, no.1, pp.13-24, 2019 (TRDizin)
- 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
- Open Archive Collection: AVESIS Open Access Collection
- 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.