Used Car Price Estimation: Moving From Linear Regression Towards A New S-Curve Model
A simple linear regression is commonly used as a practical predictive model on a used car price. It is a useful model which carry smaller prediction errors around its central mean. Practically, real data will hardly produce a linear relationship. A non-linear model has been observed to better foreca...
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| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Universiti Malaysia Sarawak
2021
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| Online Access: | http://eprints.utem.edu.my/id/eprint/25720/2/4293-ARTICLE%20TEXT-13969-1-10-20211213.PDF http://eprints.utem.edu.my/id/eprint/25720/ https://publisher.unimas.my/ojs/index.php/IJBS/article/view/4293 |
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| Summary: | A simple linear regression is commonly used as a practical predictive model on a used car price. It is a useful model which carry smaller prediction errors around its central mean. Practically, real data will hardly produce a linear relationship. A non-linear model has been observed to better forecast any price appreciation and manage prediction errors in real-life phenomena. In this paper, an S-curve model shall be proposed as an alternative non-linear model in estimating the price of used cars. A dynamic S-shaped Membership Function (SMF) is used as a basis to build an S-curve pricing model in this research study. Real used car price data has been collected from a popular website. Comparisons against linear regression and cubic regression are made. An S-curve model has produced smaller error than linear regression while its residual is closer to a cubic regression. Overall, an S-curve model is anticipated to provide a better and more practical estimate on used car prices in Malaysia. |
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