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

Content Provider	IEEE Xplore Digital Library
Author	Tay Sze Hui Rahman, S.A. Labadin, J.
Copyright Year	2013
Description	Author affiliation: Dept. of Comput. Sci. & Math., Univ. Malaysia Sarawak, Kota Samarahan, Malaysia (Tay Sze Hui; Rahman, S.A.; Labadin, J.)
Abstract	Global warming due to the rapid increase in greenhouse gas emissions, mainly carbon dioxide $(CO_{2}),$ 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 $CO_{2}$ 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 $CO_{2}$ emissions. In overall, MARS can be viewed as a modification of stepwise regression that enhances the latter's performance in the regression setting.
Starting Page	1
Ending Page	5
File Size	1346879
Page Count	5
File Format	PDF
e-ISBN	9781479910922
DOI	10.1109/CITA.2013.6637554
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-01
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Mars Adaptation models Biological system modeling Computational modeling CO2 emissions Predictive models Data models ASEAN Splines (mathematics) Multivariate adaptive regression splines Multiple regression
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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