Spatial and spatio temporal geostatistical modeling and kriging 4.7.1 Direct residual kriging 4.7.2 Iterative residual kriging 4.7.3 Modified iterative residual kriging 4.8 Median Polish kriging 4.9 Cross validation 4.10 Non linear kriging 4.10.1 Disjunctive kriging 4.10.2 Indicator kriging Chapter 5 Geostatistics and spatio temporal random functions 5.1 Spatio temporal geostatistics 5.2 Spatio temporal continuity 5.3 Relevant spatio temporal concepts 5.4 Properties of the spatio temporal covariance and semivariogram 2.3 Stationary and intrinsic hypotheses 2.3.1 Stationarity 2.3.2 Stationary random functions in the strict sense 2.3.3 Second order stationary random functions 2.3.4 Intrinsically stationary random functions 2.3.5 Non stationary random functions 2.4 Support Chapter 3 Structural analysis 3.1 Introduction 3.2 Covariance function 3.2.1 Definition and properties 3.2.2 Some theoretical isotropic covariance functions 3.3 Empirical covariogram 3.4 Semivariogram 3.4.1 Definition and properties Cover Title Page Copyright Dedication Contents Foreword by Abdel H. El Shaarawi Foreword by Hao Zhang List of figures List of tables About the companion website Chapter 1 From classical statistics to geostatistics 1.1 Not all spatial data are geostatistical data 1.2 The limits of classical statistics 1.3 A real geostatistical dataset: data on carbon monoxide in Madrid Spain Chapter 2 Geostatistics: preliminaries 2.1 Regionalized variables 2.2 Random functions 4.3.1 Point observation support and point predictor 4.3.2 Effects of a change in the model parameters 4.3.3 Point observation support and block predictor 4.3.4 Block observation support and block predictor 4.4 Simple kriging: the special case of known mean 4.5 Simple kriging with an estimated mean 4.6 Universal kriging 4.6.1 Point observation support and point predictor 4.6.2 Point observation support and block predictor 4.6.3 Block observation support and block predictor 4.6.4 Kriging and exact interpolation 4.7 Residual kriging 3.4.2 Behavior at intermediate and large distances 3.4.3 Behavior near the origin 3.4.4 A discontinuity at the origin 3.5 Theoretical semivariogram models 3.5.1 Semivariograms with a sill 3.5.2 Semivariograms with a hole effect 3.5.3 Semivariograms without a sill 3.5.4 Combining semivariogram models 3.6 Empirical semivariogram 3.7 Anisotropy 3.8 Fitting a semivariogram model 3.8.1 Manual fitting 3.8.2 Automatic fitting Chapter 4 Spatial prediction and kriging 4.1 Introduction 4.2 Neighborhood 4.3 Ordinary kriging Chapter 6 Spatio temporal structural analysis (I): empirical semivariogram and covariogram estimation and model fitting