A study on using robust hedonic regression implementation

Authors : Serdar Cihat GÖREN, Olcay ARSLAN

Pages : 551-562

Doi:10.31801/cfsuasmas.1187009

View : 32 | Download : 55

Publication Date : 2023-06-23

Article Type : Research Paper

Abstract :This article aims to determine the features affecting the price of a product with the hedonic regression model and to estimate the contribution of each feature to the price by using robust regression estimation methods. For the analysis, the price and feature information of the laptop product group were obtained from the big data source by using the web scraping method. Four alternatives of the hedonic regression model are used to determine the features affecting the price of the laptops. The contribution of each feature to the laptop price is estimated by using the robust insert ignore into journalissuearticles values(Huber M-estimator); estimation method and the Ordinary Least Squares insert ignore into journalissuearticles values(OLS); estimation method, and the resulting estimates are compared for both methods. In the framework of the data set used in the study, it is observed that the effective model is the Logarithmic Robust Hedonic Regression Model.
Keywords : Robust regression, hedonic regression, big data