Interpolation performance of a spatio-temporal model with spatially varying coefficients: application to PM10 concentrations in Rio de Janeiro
- 1 June 2005
- journal article
- Published by Springer Nature in Environmental and Ecological Statistics
- Vol. 12 (2), 169-193
- https://doi.org/10.1007/s10651-005-1040-7
Abstract
No abstract availableKeywords
This publication has 18 references indexed in Scilit:
- A Spatiotemporal Model for Mexico City Ozone LevelsJournal of the Royal Statistical Society Series C: Applied Statistics, 2004
- Study of the space–time effects in the concentration of airborne pollutants in the Metropolitan Region of Rio de JaneiroEnvironmetrics, 2003
- Space–Time Calibration of Radar Rainfall DataJournal of the Royal Statistical Society Series C: Applied Statistics, 2001
- A Multivariate Time Series Model for the Analysis and Prediction of Carbon Monoxide Atmospheric ConcentrationsJournal of the Royal Statistical Society Series C: Applied Statistics, 2001
- Bayesian Prediction of Transformed Gaussian Random FieldsJournal of the American Statistical Association, 1997
- A space‐time analysis of ground‐level ozone dataEnvironmetrics, 1994
- An Approach to Statistical Spatial-Temporal Modeling of Meteorological FieldsJournal of the American Statistical Association, 1994
- Regional Trends in Sulfate Wet DepositionJournal of the American Statistical Association, 1993
- Interpolation with uncertain spatial covariances: A Bayesian alternative to KrigingJournal of Multivariate Analysis, 1992
- The variability of rainfall acidityThe Canadian Journal of Statistics / La Revue Canadienne de Statistique, 1983