Spatial regression using kernel averaged predictors

DOI10.1007/s13253-010-0050-6zbMath1306.62286OpenAlexW2092889090MaRDI QIDQ2261002

Alan E. Gelfand, Matthew J. Heaton

Publication date: 6 March 2015

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

Full work available at URL: https://doi.org/10.1007/s13253-010-0050-6

zbMATH Keywords

spatial linear modelmultivariate Gaussian processblock averagingcircular neighborhoodsdistributed covariates

Mathematics Subject Classification ID

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

Related Items

Spatiotemporal lagged models for variable rate irrigation in agriculture

Uses Software

• spBayes
• Gibbsit

Cites Work

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• Local linear regression for functional predictor and scalar response
• Spatial variation. 2nd ed
• Hierarchical Bayesian modeling in the environmental sciences
• Nonstationary multivariate process modeling through spatially varying coregionalization
• Multivariate spatial modeling for geostatistical data using convolved covariance functions
• Approximate Bayesian Inference for Latent Gaussian models by using Integrated Nested Laplace Approximations
• A kernel-based spectral model for non-Gaussian spatio-temporal processes
• Gaussian Predictive Process Models for Large Spatial Data Sets
• Model-Based Geostatistics
• Spatial Modeling With Spatially Varying Coefficient Processes
• The Brunn-Minkowski inequality
• Bayesian Measures of Model Complexity and Fit
• Inconsistent Estimation and Asymptotically Equal Interpolations in Model-Based Geostatistics
• A Kernel-Based Spatio-Temporal Dynamical Model for Nowcasting Weather Radar Reflectivities