A dynamic spatial filtering approach to mitigate underestimation bias in field calibrated low-cost sensor air pollution data

DOI10.1214/23-AOAS1751arXiv2203.14775OpenAlexW4388085858MaRDI QIDQ6138622

Roger D. Peng, Drew R. Gentner, Claire Heffernan, Abhirup Datta, Kirsten Koehler

Publication date: 16 January 2024

Published in: The Annals of Applied Statistics (Search for Journal in Brave)

Full work available at URL: https://arxiv.org/abs/2203.14775

zbMATH Keywords

spatial statisticsGaussian processair pollutionBayesianlow-cost sensors

Mathematics Subject Classification ID

Applications of statistics (62Pxx)

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