Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor
This study presents the Generalized Space-Time Autoregressive (GSTAR) model, a multivariate time series approach that integrates spatial and temporal observations for data forecasting. This study's primary objective is to develop and apply the GSTAR model to forecast the Air Pollutant Index (AP...
| Main Authors: | , , |
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| Format: | Article |
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Universiti Kebangsaan Malaysia
2023
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| Online Access: | http://psasir.upm.edu.my/id/eprint/108087/ |
| _version_ | 1848865069510688768 |
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| author | Mohamed, Nur Maisara Abd Rahman, Nur Haizum Zulkafli, Hani Syahida |
| author_facet | Mohamed, Nur Maisara Abd Rahman, Nur Haizum Zulkafli, Hani Syahida |
| author_sort | Mohamed, Nur Maisara |
| building | UPM Institutional Repository |
| collection | Online Access |
| description | This study presents the Generalized Space-Time Autoregressive (GSTAR) model, a multivariate time series approach that integrates spatial and temporal observations for data forecasting. This study's primary objective is to develop and apply the GSTAR model to forecast the Air Pollutant Index (API), which exhibits spatial-temporal dependencies between locations and time. Three areas in Selangor have been used in this study: Banting, Petaling, and Shah Alam. The model employs uniform and inverse distance weights to consider spatial relationships. The forecasting performance is assessed using Root Mean Square Error (RMSE). Although both weight methods yield comparable results, the GSTAR model with inverse distance weight is promising for API data forecasting with consistently low RMSE values. The result of this study emphasises the significance of location-based information in generating more efficient and informed solutions. |
| first_indexed | 2025-11-15T13:58:51Z |
| format | Article |
| id | upm-108087 |
| institution | Universiti Putra Malaysia |
| institution_category | Local University |
| last_indexed | 2025-11-15T13:58:51Z |
| publishDate | 2023 |
| publisher | Universiti Kebangsaan Malaysia |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | upm-1080872024-09-10T07:35:26Z http://psasir.upm.edu.my/id/eprint/108087/ Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor Mohamed, Nur Maisara Abd Rahman, Nur Haizum Zulkafli, Hani Syahida This study presents the Generalized Space-Time Autoregressive (GSTAR) model, a multivariate time series approach that integrates spatial and temporal observations for data forecasting. This study's primary objective is to develop and apply the GSTAR model to forecast the Air Pollutant Index (API), which exhibits spatial-temporal dependencies between locations and time. Three areas in Selangor have been used in this study: Banting, Petaling, and Shah Alam. The model employs uniform and inverse distance weights to consider spatial relationships. The forecasting performance is assessed using Root Mean Square Error (RMSE). Although both weight methods yield comparable results, the GSTAR model with inverse distance weight is promising for API data forecasting with consistently low RMSE values. The result of this study emphasises the significance of location-based information in generating more efficient and informed solutions. Universiti Kebangsaan Malaysia 2023 Article PeerReviewed Mohamed, Nur Maisara and Abd Rahman, Nur Haizum and Zulkafli, Hani Syahida (2023) Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor. Journal of Quality Measurement and Analysis, 19 (3). pp. 143-153. ISSN 1823-5670; ESSN: 2600-8602 https://www.ukm.my/jqma/jqma19-3/ |
| spellingShingle | Mohamed, Nur Maisara Abd Rahman, Nur Haizum Zulkafli, Hani Syahida Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor |
| title | Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor |
| title_full | Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor |
| title_fullStr | Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor |
| title_full_unstemmed | Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor |
| title_short | Generalized space-time autoregressive (GSTAR) for forecasting Air Pollutant Index in Selangor |
| title_sort | generalized space-time autoregressive (gstar) for forecasting air pollutant index in selangor |
| url | http://psasir.upm.edu.my/id/eprint/108087/ http://psasir.upm.edu.my/id/eprint/108087/ |