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Geostatistics for Compositional Data with R

Af: Raimon Tolosana-Delgado, Ute Mueller Engelsk Paperback

Geostatistics for Compositional Data with R

Af: Raimon Tolosana-Delgado, Ute Mueller Engelsk Paperback
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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.

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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.

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Produktdetaljer
Sprog: Engelsk
Sider: 259
ISBN-13: 9783030825706
Indbinding: Paperback
Udgave:
ISBN-10: 3030825701
Kategori: Økologi, biosfæren
Udg. Dato: 21 nov 2022
Længde: 0mm
Bredde: 155mm
Højde: 235mm
Forlag: Springer Nature Switzerland AG
Oplagsdato: 21 nov 2022
Forfatter(e): Raimon Tolosana-Delgado, Ute Mueller
Forfatter(e) Raimon Tolosana-Delgado, Ute Mueller

Kategori Økologi, biosfæren

ISBN-13 9783030825706

Sprog Engelsk

Indbinding Paperback

Sider 259

Udgave

Længde 0mm

Bredde 155mm

Højde 235mm

Udg. Dato 21 nov 2022

Oplagsdato 21 nov 2022

Forlag Springer Nature Switzerland AG

Kategori sammenhænge