Modeling multivariable air pollution data in Malaysia using vector autoregressive model

In this study, the vector autoregressive (VAR) model was used to model and forecast the multivariable air pollution data in Klang area. Stationary test, Hannan–Quinn evaluation criteria, Granger causality test, R2 coefficient and Root Square Mean Error (RMSE) measurements have been conducted to get...

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Main Authors:	'Ulya Abdul Rahim, Nurulkamal Masseran
Format:	Article
Language:	English
Published:	Penerbit Universiti Kebangsaan Malaysia 2019
Online Access:	http://journalarticle.ukm.my/13875/ http://journalarticle.ukm.my/13875/ http://journalarticle.ukm.my/13875/1/jqma-15-2-paper8.pdf

id	ukm-13875
recordtype	eprints
spelling	ukm-138752020-01-08T09:26:02Z http://journalarticle.ukm.my/13875/ Modeling multivariable air pollution data in Malaysia using vector autoregressive model 'Ulya Abdul Rahim, Nurulkamal Masseran, In this study, the vector autoregressive (VAR) model was used to model and forecast the multivariable air pollution data in Klang area. Stationary test, Hannan–Quinn evaluation criteria, Granger causality test, R2 coefficient and Root Square Mean Error (RMSE) measurements have been conducted to get the best model and will be used in forecasting. The VAR (7) model is found to be the best model with the highest R2 and lowest RMSE value recorded for each dependent pollutant variable. Based on the fitted VAR (7) model, the VAR model is able to describe the dynamic behavior of multivariable air pollution data of Klang. Forecasts of up to 12 days ahead were constructed with confidence intervals. The VAR model found to provides good forecast accuracy on the data. Penerbit Universiti Kebangsaan Malaysia 2019-12 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/13875/1/jqma-15-2-paper8.pdf 'Ulya Abdul Rahim, and Nurulkamal Masseran, (2019) Modeling multivariable air pollution data in Malaysia using vector autoregressive model. Journal of Quality Measurement and Analysis, 15 (2). pp. 85-93. ISSN 1823-5670 http://www.ukm.my/jqma/current.html
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Kebangasaan Malaysia
building	UKM Institutional Repository
collection	Online Access
language	English
description	In this study, the vector autoregressive (VAR) model was used to model and forecast the multivariable air pollution data in Klang area. Stationary test, Hannan–Quinn evaluation criteria, Granger causality test, R2 coefficient and Root Square Mean Error (RMSE) measurements have been conducted to get the best model and will be used in forecasting. The VAR (7) model is found to be the best model with the highest R2 and lowest RMSE value recorded for each dependent pollutant variable. Based on the fitted VAR (7) model, the VAR model is able to describe the dynamic behavior of multivariable air pollution data of Klang. Forecasts of up to 12 days ahead were constructed with confidence intervals. The VAR model found to provides good forecast accuracy on the data.
format	Article
author	'Ulya Abdul Rahim, Nurulkamal Masseran,
spellingShingle	'Ulya Abdul Rahim, Nurulkamal Masseran, Modeling multivariable air pollution data in Malaysia using vector autoregressive model
author_facet	'Ulya Abdul Rahim, Nurulkamal Masseran,
author_sort	'Ulya Abdul Rahim,
title	Modeling multivariable air pollution data in Malaysia using vector autoregressive model
title_short	Modeling multivariable air pollution data in Malaysia using vector autoregressive model
title_full	Modeling multivariable air pollution data in Malaysia using vector autoregressive model
title_fullStr	Modeling multivariable air pollution data in Malaysia using vector autoregressive model
title_full_unstemmed	Modeling multivariable air pollution data in Malaysia using vector autoregressive model
title_sort	modeling multivariable air pollution data in malaysia using vector autoregressive model
publisher	Penerbit Universiti Kebangsaan Malaysia
publishDate	2019
url	http://journalarticle.ukm.my/13875/ http://journalarticle.ukm.my/13875/ http://journalarticle.ukm.my/13875/1/jqma-15-2-paper8.pdf
first_indexed	2023-09-18T20:05:50Z
last_indexed	2023-09-18T20:05:50Z
_version_	1777407151538438144

Modeling multivariable air pollution data in Malaysia using vector autoregressive model

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