A Novel S-Regression Model on an Auto Price

Abstract

A simple linear regression model is useful in a prediction model. A general linear regression beyond a single independent variable is still not popular. A nonlinear regression can be easily produced a better predictive model but it is difficult to construct. The objective of this paper is to propose a technique for predicting the price of used cars in Malaysia using S-shaped curve model. In this paper, the S-shaped Membership Function [SMF] is used as the basis to develop a novel S-Regression model. Comparisons between linear regression, cubic regression and S-Regression have been made on the used car prices. The mean squared error of S-Regression model is found to be closer to cubic regression than the linear regression. S-Regression model is found to be quite suitable to represent the relationship between the price of a used car and the make year of a car. The result demonstrates that the S-Regression model gives better and practical estimate of the price of a used car in Malaysia.

Used Car Price Estimation: Moving from Linear Regression towards a New S-Curve Model

“…An immediate objective of this research study is to construct a new S-curve model as a practical tool to estimate on a price of a used car. A preliminary research prior to this research study has been carried out to establish a new S-curve model for better and practical estimation on a used car price (Salim & Abu, 2018). Hence, this study is an extension to Salim and Abu (2018) by using a different data set to validate the model.…”

“…A preliminary research prior to this research study has been carried out to establish a new S-curve model for better and practical estimation on a used car price (Salim & Abu, 2018). Hence, this study is an extension to Salim and Abu (2018) by using a different data set to validate the model. In addition, this paper will highlight an incremental development on an S-curve model based on the S-shaped Membership Function.…”