Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries

Tay, Sze Hui and Shapiee, Abd Rahman and Jane, Labadin (2013) Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries. In: 2013 8th International Conference on Information Technology in Asia (CITA), 1-4 July 2013, Kota Samarahan.

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Abstract

Global warming due to the rapid increase in greenhouse gas emissions, mainly carbon dioxide (CO2), is a worldwide issue that leads to escalating pollutions and emerging diseases. The comparative performances of multiple regression (MR) and multivariate adaptive regression splines (MARS) for statistical modelling of CO2 emissions are analyzed in ASEAN countries over the period of 1980-2007. The regression models are fitted individually for every potential variable investigated so as to find the best-fit parametric or non-parametric model. The results show a significant difference between the performance of MR and MARS models with the inclusion of interaction terms. The MARS model is computationally feasible and has better predictive ability than the MR model in predicting CO2 emissions. In overall, MARS can be viewed as a modification of stepwise regression that enhances the latter's performance in the regression setting.

Item Type: Proceeding (Paper)
Uncontrolled Keywords: Adaptation models, Biological system modeling, Computational modeling, Data models, Mars, Predictive models,Splines,(mathematics), unimas, university, universiti, Borneo, Malaysia, Sarawak, Kuching, Samarahan, ipta, education, research, Universiti Malaysia Sarawak
Subjects: T Technology > TD Environmental technology. Sanitary engineering
Divisions: Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Faculties, Institutes, Centres > Faculty of Computer Science and Information Technology
Academic Faculties, Institutes and Centres > Faculty of Computer Science and Information Technology
Depositing User: Karen Kornalius
Date Deposited: 05 Aug 2015 01:02
Last Modified: 04 Jan 2022 04:38
URI: http://ir.unimas.my/id/eprint/8473

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