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

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 statisti...

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Main Authors: Tay, Sze Hui, Shapiee, Abd Rahman, Jane, Labadin
Format: Proceeding
Language:English
Published: 2013
Subjects:
Online Access:http://ir.unimas.my/id/eprint/8473/
http://ir.unimas.my/id/eprint/8473/1/Tay%20Sze%20Hui.pdf
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author Tay, Sze Hui
Shapiee, Abd Rahman
Jane, Labadin
author_facet Tay, Sze Hui
Shapiee, Abd Rahman
Jane, Labadin
author_sort Tay, Sze Hui
building UNIMAS Institutional Repository
collection Online Access
description 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.
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institution Universiti Malaysia Sarawak
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language English
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publishDate 2013
recordtype eprints
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spelling unimas-84732022-01-04T04:38:33Z http://ir.unimas.my/id/eprint/8473/ Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries Tay, Sze Hui Shapiee, Abd Rahman Jane, Labadin TD Environmental technology. Sanitary engineering 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. 2013 Proceeding NonPeerReviewed text en http://ir.unimas.my/id/eprint/8473/1/Tay%20Sze%20Hui.pdf 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. http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6637554
spellingShingle TD Environmental technology. Sanitary engineering
Tay, Sze Hui
Shapiee, Abd Rahman
Jane, Labadin
Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries
title Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries
title_full Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries
title_fullStr Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries
title_full_unstemmed Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries
title_short Comparison between multiple regression and multivariate adaptive regression splines for predicting CO2 emissions in ASEAN countries
title_sort comparison between multiple regression and multivariate adaptive regression splines for predicting co2 emissions in asean countries
topic TD Environmental technology. Sanitary engineering
url http://ir.unimas.my/id/eprint/8473/
http://ir.unimas.my/id/eprint/8473/
http://ir.unimas.my/id/eprint/8473/1/Tay%20Sze%20Hui.pdf