A practical approach for assessing the effect of grouping in hierarchical spatio-temporal models

DOI10.1007/s10182-012-0193-6zbMath1443.62400OpenAlexW2019105845MaRDI QIDQ1621224

Francesca Bruno, Lucia Paci, Daniela Cocchi

Publication date: 8 November 2018

Published in: AStA. Advances in Statistical Analysis (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10182-012-0193-6

zbMATH Keywords

tropospheric ozonehierarchical modelsspatio-temporal modelsgroups of spatial sites

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Inference from spatial processes (62M30) Applications of statistics to environmental and related topics (62P12) Bayesian inference (62F15) Geostatistics (86A32)

Related Items (2)

Spatial statistics for environmental studies ⋮ Dynamic model-based clustering for spatio-temporal data

Uses Software

• WinBUGS
• spBayes

Cites Work

• Unnamed Item
• Unnamed Item
• Unnamed Item
• Unnamed Item
• High-Resolution Space–Time Ozone Modeling for Assessing Trends
• Model choice: a minimum posterior predictive loss approach
• Bayesian Measures of Model Complexity and Fit
• Considering groups in the statistical modeling of spatio-temporal data
• Linear and Generalized Linear Models and their Applications by J. JIANG
• Statistical Methods for Spatio-Temporal Systems

This page was built for publication: A practical approach for assessing the effect of grouping in hierarchical spatio-temporal models