This book presents an introduction to geostatistics stressing the multivariate aspects for scientists, engineers or statisticians. Geostatistics offers a variety of models, methods and techniques for the analysis, estimation and display of multivariate data distributed in space or time. This book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics and an account of three basic methods of multivariate analysis. The third edition of this very successful textbook contains an advanced presentation of linear models for multivariate spatial or temporal data, of nonlinear models and methods for selection problems with change of suppport as well as an introduction to non-stationary geostatistics with special focus on the external drift method. Applications from diverse areas of science, as well as exercises with solutions, are provided to help convey the concepts and techniques.

Detailed treatment of multivariate geostatistics Introduction to linear geostatistics Introduction to non-stationary geostatistics Includes supplementary material: sn.pub/extras

Klappentext

The third edition of this very successful text book provides an introduction to geostatistics stressing the multivariate aspects for scientists, engineers or statisticians. Geostatistics offers a variety of models, methods and techniques for the analysis, estimation and display of multivariate data distributed in space or time. This book presents a brief review of statistical concepts, a detailed introduction to linear geostatistics, and an account of three methods of multivariate analysis. Moreover, it contains an advanced presentation of linear models for mulitvariate spatial or temporal data, of nonlinear models and methods for selection problems with change of support, as well as an introduction to non-stationary geostatistics with special focus on the external drift method. Applications from very different areas of science as well as exercices with solutions are provided to help convey the general ideas.

Inhalt
1 Introduction.- 2 Mean, Variance, Covariance.- 3 Linear Regression and Simple Kriging.- 4 Kriging the Mean.- 5 Regionalized Variable and Random Function.- 6 Variogram Cloud.- 7 Variogram and Covariance Function.- 8 Examples of Covariance Functions.- 9 Anisotropy.- 10 Extension and Dispersion Variance.- 11 Ordinary Kriging.- 12 Kriging Weights.- 13 Mapping with Kriging.- 14 Linear Model of Regionalization.- 15 Kriging Spatial Components.- 16 The Smoothness of Kriging.- 17 Principal Component Analysis.- 18 Canonical Analysis.- 19 Correspondence Analysis.- 20 Direct and Cross Covariances.- 21 Covariance Function Matrices.- 22 Intrinsic Multivariate Correlation.- 23 Heterotopic Cokriging.- 24 Collocated Cokriging.- 25 Isotopic Cokriging.- 26 Multivariate Nested Variogram.- 27 Case Study: Ebro Estuary.- 28 Coregionalization Analysis.- 29 Kriging a Complex Variable.- 30 Bilinear Coregionalization Model.- 31 Thresholds and Selectivity Curves.- 32 Lognormal Estimation.- 33 Gaussian Anamorphosis with Hermite Polynomials.- 34 Isofactorial Models.- 35 Isofactorial Change of Support.- 36 Kriging with Discrete Point-Bloc Models.- 37 External Drift.- 38 Universal Kriging.- 39 Translation Invariant Drift.- Matrix Algebra.- Linear Regression Theory.- Covariance and Variogram Models.- Additional Exercices.- Solutions to Exercises.- References.