Bayesian spatiotemporal modeling for estimating short-term exposure to air pollution in Santiago de Chile

DOI10.1002/env.2574zbMATH Open1545.62882MaRDI QIDQ6626094

Sandeep Kumar Sahu, Julio Marín, Orietta Nicolis, Mailiu Diaz

Publication date: 28 October 2024

Published in: Environmetrics (Search for Journal in Brave)

zbMATH Keywords

forecastingspatiotemporal modeling\(PM_{2.5}\) pollutionWRF model

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12)

Cites Work

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• Dynamic Models for Spatiotemporal Data
• Modelling Daily Multivariate Pollutant Data at Multiple Sites
• High-Resolution Space–Time Ozone Modeling for Assessing Trends
• Model choice: a minimum posterior predictive loss approach
• A dimension-reduced approach to space-time Kalman filtering
• A Bayesian Kriged Kalman Model for Short-Term Forecasting of Air Pollution Levels
• Geostatistical space-time models: a review

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