Hierarchical Bayesian spatio-temporal modeling for \(\mathrm{PM}_{10}\) prediction

DOI10.1155/2021/8003952zbMath1499.62424OpenAlexW3199182262MaRDI QIDQ2241277

Esam Mahdi, Maryam Khashabi, Sana Alshamari, Alya Alkorbi

Publication date: 8 November 2021

Published in: Journal of Applied Mathematics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2021/8003952

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Geostatistics (86A32)

Uses Software

• mgcv
• ElemStatLearn
• gamair
• spTimer

Cites Work

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• Modelling Daily Multivariate Pollutant Data at Multiple Sites
• Sampling-Based Approaches to Calculating Marginal Densities
• High-Resolution Space–Time Ozone Modeling for Assessing Trends
• An Approach to Statistical Spatial-Temporal Modeling of Meteorological Fields
• Bayesian Spatial Prediction of Random Space-Time Fields With Application to Mapping PM_2.5Exposure
• A Bayesian Kriged Kalman Model for Short-Term Forecasting of Air Pollution Levels
• The elements of statistical learning. Data mining, inference, and prediction

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