Tolosana-Delgado R., Mueller U. Geostatistics for Compositional Data with R

Springer, 2021. — 275 p. — (UseR!). — ISBN: 978-3-030-82567-6.This book provides a guided approach to the geostatistical modeling of compositional spatial data. These data are data in proportions, percentages, or concentrations distributed in space that exhibit spatial correlation. The book can be divided into four blocks. The first block sets the framework and provides some background on compositional data analysis. Block two introduces compositional exploratory tools for both non-spatial and spatial aspects. Block three covers all necessary facets of multivariate spatial prediction for compositional data: variogram modeling, cokriging, and validation. Finally, block four detailed strategies for simulation of compositional data, including transformations to multivariate normality, Gaussian simulation, multipoint simulation of compositional data, and common postprocessing techniques, valid for both Gaussian and multipoint methods.A Review of Compositional Data Analysis
Exploratory Data Analysis
Exploratory Spatial Analysis
VariogramModels
Geostatistical Estimation
Cross-Validation
Multivariate Normal Score Transformation
Simulation
Compositional Direct Sampling Simulation
Evaluation and Postprocessing of ResultsMatrix Decompositions
Complete Data AnalysisWorkflows