Multivariate spatial-temporal modeling and prediction of speciated fine particles

DOI10.1080/15598608.2009.10411933zbMath1211.62091OpenAlexW2016476433WikidataQ33795226 ScholiaQ33795226MaRDI QIDQ2431686

Jungsoon Choi, Brian J. Reich, Montserrat Fuentes, Jerry Davis

Publication date: 18 April 2011

Published in: Journal of Statistical Theory and Practice (Search for Journal in Brave)

Full work available at URL: http://europepmc.org/articles/pmc2856093

zbMATH Keywords

air pollutionBayesian inferencelinear coregionalization model: multivariate spatiotemporal processesspeciated particulate matter

Mathematics Subject Classification ID

Directional data; spatial statistics (62H11) Linear regression; mixed models (62J05) Applications of statistics to biology and medical sciences; meta analysis (62P10) Applications of statistics to environmental and related topics (62P12)

Related Items (8)

Prediction of particle pollution through spatio-temporal multivariate geostatistical analysis: spatial special issue ⋮ Non-stationary Cross-Covariance Models for Multivariate Processes on a Globe ⋮ Multivariate spatio‐temporal modelling for assessing Antarctica's present‐day contribution to sea‐level rise ⋮ A data fusion approach for spatial analysis of speciated PM_2.5 across time ⋮ Matérn-based nonstationary cross-covariance models for global processes ⋮ Stationary and isotropic vector random fields on spheres ⋮ Using simultaneous diagonalization to identify a space-time linear coregionalization model ⋮ Cross-covariance functions for multivariate geostatistics

Cites Work

• Spatial Association between Speciated Fine Particles and Mortality
• Bayesian Measures of Model Complexity and Fit
• Unnamed Item

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