A genetic algorithm for robust regression in linear models

Home Page
About
Submit A Journal
Submit A Conference
Submit Paper/Book
- Submit a Preprint
- Submit a Book
Contact

İstatistikçiler Dergisi:İstatistik ve Aktüerya
Cilt: 18 Sayı: 1
A genetic algorithm for robust regression in linear models

A genetic algorithm for robust regression in linear models

Authors : Ahmet Toy, Erol Terzi

Pages : 1-15

View : 77 | Download : 33

Publication Date : 2025-06-29

Article Type : Research Paper

Abstract :Outliers negatively affect the parameter estimate. Therefore, observation values can be weighted to minimize the negative impact of outliers on the parameter estimate. In this study, a robust method is proposed in which observation values are weighted with Genetic Algorithm (GA), which can be used both for outlier detection and parameter estimation. The proposed Genetic Algorithm for Robust Regression (GA-RR) method and M-estimators were compared to the root mean square error (RMSE) and mean absolute error (MAE) performance criterion using simulation study. Furthermore, the performance of the methods was evaluated using real data.
Keywords : Robust Regresyon, M-Tahminciler, Genetik Algoritma, Aykırı Değer

ORIGINAL ARTICLE URL

* There may have been changes in the journal, article,conference, book, preprint etc. informations. Therefore, it would be appropriate to follow the information on the official page of the source. The information here is shared for informational purposes. IAD is not responsible for incorrect or missing information.