Use R!
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Geostatistics for Compositional Data with R

Authors: Tolosana-Delgado, Raimon, Mueller, Ute

  • 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"
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eBook 85,59 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: November 9, 2021
  • ISBN 978-3-030-82568-3
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 103,99 €
price for Spain (gross)
  • Due: November 9, 2021
  • ISBN 978-3-030-82567-6
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • The final prices may differ from the prices shown due to specifics of VAT rules
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.

About the authors

Raimon Tolosana-Delgado is a senior scientist from the department of modelling and valuation at Helmholtz Institute Freiberg, Germany. He is a specialist in compositional data analysis, applied multivariate geostatistics, and applications of statistics, data analysis and machine learning in geology as well as in the mining and minerals industry. His current focus is on predictive geometallurgy.

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. 

Buy this book

eBook 85,59 €
price for Spain (gross)
  • The eBook version of this title will be available soon
  • Due: November 9, 2021
  • ISBN 978-3-030-82568-3
  • Digitally watermarked, DRM-free
  • Included format:
  • ebooks can be used on all reading devices
Hardcover 103,99 €
price for Spain (gross)
  • Due: November 9, 2021
  • ISBN 978-3-030-82567-6
  • Free shipping for individuals worldwide
  • Institutional customers should get in touch with their account manager
  • Covid-19 shipping restrictions
  • The final prices may differ from the prices shown due to specifics of VAT rules
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Bibliographic Information

Bibliographic Information
Book Title
Geostatistics for Compositional Data with R
Authors
Series Title
Use R!
Copyright
2021
Publisher
Springer International Publishing
Copyright Holder
Springer Nature Switzerland AG
eBook ISBN
978-3-030-82568-3
DOI
10.1007/978-3-030-82568-3
Hardcover ISBN
978-3-030-82567-6
Series ISSN
2197-5736
Edition Number
1
Number of Pages
X, 286
Number of Illustrations
104 b/w illustrations
Topics