High-Resolution Spatiotemporal Forecasting with Missing Observations Including an Application to Daily Particulate Matter 2.5 Concentrations in Jakarta Province, Indonesia
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- Michela Cameletti & Finn Lindgren & Daniel Simpson & Håvard Rue, 2013. "Spatio-temporal modeling of particulate matter concentration through the SPDE approach," AStA Advances in Statistical Analysis, Springer;German Statistical Society, vol. 97(2), pages 109-131, April.
- Prakash Thangavel & Duckshin Park & Young-Chul Lee, 2022. "Recent Insights into Particulate Matter (PM 2.5 )-Mediated Toxicity in Humans: An Overview," IJERPH, MDPI, vol. 19(12), pages 1-22, June.
- Amanda Lenzi & Ingelin Steinsland & Pierre Pinson, 2018. "Benefits of spatiotemporal modeling for short‐term wind power forecasting at both individual and aggregated levels," Environmetrics, John Wiley & Sons, Ltd., vol. 29(3), May.
- I. Gede Nyoman Mindra Jaya & Budhi Handoko & Yudhie Andriyana & Anna Chadidjah & Farah Kristiani & Mila Antikasari, 2023. "Multivariate Bayesian Semiparametric Regression Model for Forecasting and Mapping HIV and TB Risks in West Java, Indonesia," Mathematics, MDPI, vol. 11(17), pages 1-23, August.
- Widya Liadira Kusuma & Wu Chih-Da & Zeng Yu-Ting & Handayani Hepi Hapsari & Jaelani Lalu Muhamad, 2019. "PM 2.5 Pollutant in Asia—A Comparison of Metropolis Cities in Indonesia and Taiwan," IJERPH, MDPI, vol. 16(24), pages 1-12, December.
- Håvard Rue & Sara Martino & Nicolas Chopin, 2009. "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 71(2), pages 319-392, April.
- David J. Spiegelhalter & Nicola G. Best & Bradley P. Carlin & Angelika Van Der Linde, 2002. "Bayesian measures of model complexity and fit," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 64(4), pages 583-639, October.
- Yusuf, Arief Anshory & Resosudarmo, Budy P., 2009. "Does clean air matter in developing countries' megacities? A hedonic price analysis of the Jakarta housing market, Indonesia," Ecological Economics, Elsevier, vol. 68(5), pages 1398-1407, March.
- Finn Lindgren & Håvard Rue & Johan Lindström, 2011. "An explicit link between Gaussian fields and Gaussian Markov random fields: the stochastic partial differential equation approach," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 73(4), pages 423-498, September.
- I. Gede Nyoman Mindra Jaya & Henk Folmer, 2022. "Spatiotemporal high-resolution prediction and mapping: methodology and application to dengue disease," Journal of Geographical Systems, Springer, vol. 24(4), pages 527-581, October.
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Keywords
multivariate spatial time series model; Gaussian Markov random field (GMRF); high-resolution forecasting; Bayesian statistics; integrated nested Laplace approximation (INLA); PM 2.5 ; Jakarta;All these keywords.
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