Modelling spatio-temporal air pollution data from a mobile monitoring station

DOI10.1080/00949655.2016.1167895OpenAlexW2316690062MaRDI QIDQ5222498

David Cappelletti, Silvia Castellini, Stefano Crocchianti, Beatrice Moroni, Simone Del Sarto, Maria Giovanna Ranalli

Publication date: 1 April 2020

Published in: Journal of Statistical Computation and Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/00949655.2016.1167895

zbMATH Keywords

Bayesian hierarchical modelsenvironmental datamultiple measurementshigh-frequency time seriesair quality data

Mathematics Subject Classification ID

Statistics (62-XX)

Related Items (2)

Fine-Scale Spatiotemporal Air Pollution Analysis Using Mobile Monitors on Google Street View Vehicles ⋮ Where is the clean air? A Bayesian decision framework for personalised cyclist route selection using R-INLA

Uses Software

• spBayes
• spTimer

Cites Work

• Unnamed Item
• Editorial: Advanced methods for space-time environmental data
• Functional exploratory data analysis for high-resolution measurements of urban particulate matter
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• Gaussian Predictive Process Models for Large Spatial Data Sets
• High-Resolution Space–Time Ozone Modeling for Assessing Trends

This page was built for publication: Modelling spatio-temporal air pollution data from a mobile monitoring station