Overview
- Gives an integrated approach to geostatistical modelling of compositional data
- Modelling approaches are illustrated through detailed examples from real world data
- Presents workflows and R code for all aspects of the methodology, encapsulated in the R package "gmGeostats"
Part of the book series: Use R! (USE R)
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Table of contents (11 chapters)
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Front Matter
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Back Matter
Keywords
About this book
This book provides a guided approach to the geostatistical modelling of compositional spatial data. These data are data in proportions, percentages or concentrations distributed in space which 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 modelling, cokriging and validation. Finally, block four details strategies for simulation of compositional data, including transformations to multivariate normality, Gaussian cosimulation, multipoint simulation of compositional data, and common postprocessing techniques, valid for both Gaussian and multipoint methods.
All methods are illustrated via applications to two types of data sets: one a large-scale geochemical survey, comprised of a full suite of geochemical variables, and the other from a mining context, where only the elements of greatest importance are considered. R codes are included for all aspects of the methodology, encapsulated in the R package "gmGeostats", available in CRAN.
Authors and Affiliations
About the authors
Ute Mueller is an associate professor in mathematics at Edith Cowan University in Perth, Australia. She has been teaching geostatistics for the last twenty years and has a research background in the application of multivariate geostatistical modelling techniques in mining, fisheries and health. In the last ten years she has focussed on compositional geostatistical data in particular.
Bibliographic Information
Book Title: Geostatistics for Compositional Data with R
Authors: Raimon Tolosana-Delgado, Ute Mueller
Series Title: Use R!
DOI: https://doi.org/10.1007/978-3-030-82568-3
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: Springer Nature Switzerland AG 2021
Hardcover ISBN: 978-3-030-82567-6Published: 20 November 2021
Softcover ISBN: 978-3-030-82570-6Published: 21 November 2022
eBook ISBN: 978-3-030-82568-3Published: 19 November 2021
Series ISSN: 2197-5736
Series E-ISSN: 2197-5744
Edition Number: 1
Number of Pages: XXV, 259
Number of Illustrations: 104 b/w illustrations
Topics: Statistical Theory and Methods, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences, Theoretical Ecology/Statistics, Statistics for Life Sciences, Medicine, Health Sciences