Nonseparable, Stationary Covariance Functions for Space–Time Data
Top Cited Papers
- 1 June 2002
- journal article
- Published by Taylor & Francis in Journal of the American Statistical Association
- Vol. 97 (458) , 590-600
- https://doi.org/10.1198/016214502760047113
Abstract
Geostatistical approaches to spatiotemporal prediction in environmental science, climatology, meteorology, and related fields rely on appropriate covariance models. This article proposes general cl...Keywords
This publication has 25 references indexed in Scilit:
- Blur-generated non-separable space–time modelsJournal of the Royal Statistical Society Series B: Statistical Methodology, 2000
- On the physical geometry concept at the basis of space/time geostatistical hydrologyAdvances in Water Resources, 2000
- Product-sum covariance for space-time modeling: an environmental applicationEnvironmetrics, 2000
- Classes of Nonseparable, Spatio-Temporal Stationary Covariance FunctionsJournal of the American Statistical Association, 1999
- Ozone Exposure and Population Density in Harris County, TexasJournal of the American Statistical Association, 1997
- Ozone Exposure and Population Density in Harris County, Texas: CommentJournal of the American Statistical Association, 1997
- The dynamics of error covariances in a barotropic modelTellus A: Dynamic Meteorology and Oceanography, 1993
- A Coordinate Transformation for Objective Frontal AnalysisMonthly Weather Review, 1993
- Bayesian Prediction of Deterministic Functions, with Applications to the Design and Analysis of Computer ExperimentsJournal of the American Statistical Association, 1991
- A simple spatial-temporal model of rainfallProceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences, 1988