A distance-based method for spatial prediction in the presence of trend

DOI10.1007/s13253-020-00395-2OpenAlexW3033412526MaRDI QIDQ2209870

Carlos E. Melo, Oscar O. Melo, Jorge Mateu

Publication date: 5 November 2020

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

Full work available at URL: https://doi.org/10.1007/s13253-020-00395-2

zbMATH Keywords

Gaussian random fieldsprincipal coordinatesdistance-based universal Krigingregionalized mixed variablesunconditional simulations

Mathematics Subject Classification ID

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

Uses Software

• R-Geo
• INTAMAP
• EnviroStat
• geospt

Cites Work

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• The design and analysis of computer experiments.
• Design and analysis of computer experiments. With comments and a rejoinder by the authors
• Statistical analysis of environmental space-time processes.
• Applied Spatial Data Analysis with R
• Some computational aspects of a distance—based model for prediction
• Adding a point to vector diagrams in multivariate analysis

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