| Formatted contents note |
Introduction 1 <br/>Types of Problems Considered, 2 <br/>Description or Interpretation?, 8 <br/>1. Preliminaries 11 <br/>1.1 Random Functions, 11 <br/>1.2 On the Objectivity of Probabilistic Statements, 22 <br/>1.3 Transitive Theory, 24 <br/>2. Structural Analysis 28 <br/>2.1 General Principles, 28 <br/>2.2 Variogram Cloud and Sample Variogram, 33 <br/>2.3 Mathematical Properties of the Variogram, 59 <br/>2.4 Regularization and Nugget Effect, 78 <br/>2.5 Variogram Models, 84 <br/>2.6 Fitting a Variogram Model, 109 <br/>2.7 Variography in the Presence of a Drift, 122 <br/>2.8 Simple Applications of the Variogram, 130 <br/>2.9 Complements: Theory of Variogram Estimation and Fluctuation, 138 <br/>3. Kriging 147 <br/>3.1 Introduction, 147 <br/>3.2 Notations and Assumptions, 149 <br/>3.3 Kriging with a Known Mean, 150 <br/>3.4 Kriging with an Unknown Mean, 161 <br/>3.5 Estimation of a Spatial Average, 196 <br/>3.6 Selection of a Kriging Neighborhood, 204 <br/>3.7 Measurement Errors and Outliers, 216 <br/>3.8 Case Study: The Channel Tunnel, 225 <br/>3.9 Kriging Under Inequality Constraints, 232 <br/>4. Intrinsic Model of Order k 238 <br/>4.1 Introduction, 238 <br/>4.2 A Second Look at the Model of Universal Kriging, 240 <br/>4.3 Allowable Linear Combinations of Order k, 245 <br/>4.4 Intrinsic Random Functions of Order k, 252 <br/>4.5 Generalized Covariance Functions, 257 <br/>4.6 Estimation in the IRF Model, 269 <br/>4.7 Generalized Variogram, 281 <br/>4.8 Automatic Structure Identification, 286 <br/>4.9 Stochastic Differential Equations, 294 <br/>5. Multivariate Methods 299 <br/>5.1 Introduction, 299 <br/>5.2 Notations and Assumptions, 300 <br/>5.3 Simple Cokriging, 302 <br/>5.4 Universal Cokriging, 305 <br/>5.5 Derivative Information, 320 <br/>5.6 Multivariate Random Functions, 330 <br/>5.7 Shortcuts, 360 <br/>5.8 SpaceTime Models, 370 <br/>6. Nonlinear Methods 386 <br/>6.1 Introduction, 386 <br/>6.2 Global Point Distribution, 387 <br/>6.3 Local Point Distribution: Simple Methods, 392 <br/>6.4 Local Estimation by Disjunctive Kriging, 401 <br/>6.5 Selectivity and Support Effect, 433 <br/>6.6 Multi-Gaussian Change-of-Support Model, 445 <br/>6.7 Affine Correction, 448 <br/>6.8 Discrete Gaussian Model, 449 <br/>6.9 Non-Gaussian Isofactorial Change-of-Support Models, 466 <br/>6.10 Applications and Discussion, 469 <br/>6.11 Change of Support by the Maximum (C. Lantue´ joul), 470 <br/>7. Conditional Simulations 478 <br/>7.1 Introduction and Definitions, 478 <br/>7.2 Direct Conditional Simulation of a Continuous Variable, 489 <br/>7.3 Conditioning by Kriging, 495 <br/>7.4 Turning Bands, 502 <br/>7.5 Nonconditional Simulation of a Continuous Variable, 508 <br/>7.6 Simulation of a Categorical Variable, 546 <br/>7.7 Object-Based Simulations: Boolean Models, 574 <br/>7.8 Beyond Standard Conditioning, 590 <br/>7.9 Additional Topics, 606 <br/>7.10 Case Studies, 615 <br/>Appendix 629 <br/>References 642 <br/>Index 689 |
