Spatiotemporal event studies for environmental data under cross-sectional dependence: an application to air quality assessment in Lombardy

DOI10.1007/s13253-023-00564-zMaRDI QIDQ6656020

Matteo M. Pelagatti, Paolo Maranzano

Publication date: 31 December 2024

Published in: Journal of Agricultural, Biological and Environmental Statistics (Search for Journal in Brave)

zbMATH Keywords

multivariate time seriesair qualityevent studiesabnormal concentrationsspatial cross-sectional dependence

Mathematics Subject Classification ID

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

Cites Work

• Title not available (Why is that?)
• Title not available (Why is that?)
• Title not available (Why is that?)
• A note on the validity of cross-validation for evaluating autoregressive time series prediction
• The importance of scale for spatial-confounding bias and precision of spatial regression estimators
• Hierarchical sparse Cholesky decomposition with applications to high-dimensional spatio-temporal filtering
• Spatial autocorrelation and statistical tests: some solutions
• Functional data analysis.
• Geoadditive Models
• Equivalent sample sizes in time series regressions
• Revisiting simple linear regression with autocorrelated errors
• NOTES ON CONTINUOUS STOCHASTIC PHENOMENA
• Maximum likelihood estimation of the multivariate hidden dynamic geostatistical model with application to air quality in Apulia, Italy
• Scalable spatio-temporal smoothing via hierarchical sparse Cholesky decomposition

This page was built for publication: Spatiotemporal event studies for environmental data under cross-sectional dependence: an application to air quality assessment in Lombardy

Report a bug (only for logged in users!)Click here to report a bug for this page (MaRDI item Q6656020)