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New York : John Wiley & Sons, c1999

xi, 695 s. : il. ; 25 cm

ISBN 0-471-08315-1 (váz.)

Wiley series in probability and statistics. Applied probability and statistics section

Obsahuje bibliografii na s. 460-685, bibliografické odkazy a rejstřík

000239883

Preface ix // Abbreviations xi // Introduction 1 // Types of Problems Considered, 2 // Description or Interpretation?, 7 // 1. Preliminaries 11 // 1.1. Random Functions, 11 // 1.2. On the Objectivity of Probabilistic Statements, 22 // 1.3. Transitive Theory, 24 // 2. Structural Analysis 29 // 2.1. General Principles, 29 // 2.2. Variogram Cloud and Sample Variogram, 34 // 2.3. Mathematical Properties of the Variogram, 57 // 2.4. Regularization and Nugget Effect, 74 // 2.5. Variogram Models, 80 // 2.6. Fitting a Variogram Model, 104 // 2.7. Variography in Presence of a Drift, 115 // 2.8. Simple Applications of the Variogram, 128 // 2.9. Complements: Theory of Variogram Estimation and Fluctuation, 137 // 3. Kriging 150 // 3.1. Introduction, 150 // 3.2. Notations and Assumptions, 152 // 3.3. Kriging with a Known Mean, 154 // 3.4. Kriging with an Unknown Mean, 164 // 3.5. Estimation of a Spatial Average, 193 // 3.6. Selection of a Kriging Neighborhood, 201 // 3.7. Measurement Errors and Outliers, 210 // 3.8. Case Study: The Channel Tunnel, 215 // 3.9. Kriging under Inequality Constraints, 224 // 4. Intrinsic Model of Order ? // 4.1. IRF-0 and IRF-&, 231 // 4.2. A Second Look at the Model of Universal Kriging, 233 // 4.3. Allowable Linear Combinations of Order A:, 236 // 4.4. Intrinsic Random Functions of Order k, 243 // 4.5. Generalized Covariance Functions, 252 // 4.6. Estimation in the IRF Model, 265 // 4.7. Generalized Variogram, 276 // 4.8. Automatic Structure Identification in the General Case, 281 //

5. Multivariate Methods // 5.1. Introduction, 292 // 5.2. Notations and Assumptions, 293 // 5.3. Simple Cokriging, 296 // 5.4. Universal Cokriging, 298 // 5.5. Case of Gradient Information, 313 // 5.6. Multivariate Random Functions, 321 // 5.7. Shortcuts, 351 // 5.8. Space-Time Models, 362 // 6. Nonlinear Methods // 6.1. Introduction, 375 // 6.2. Simple Methods for Estimating a Point Distribution, 376 // 6.3. Local Estimation of a Point Distribution by Disjunctive Kriging, 388 // 6.4. Simple Methods for Estimating a Block Distribution, 419 // 6.5. Local Estimation of a Block Distribution by Disjunctive Kriging, 437 // 7. Conditional Simulations // 449 // 7.1. Introduction and Definitions, 449 // 7.2. Direct Conditional Simulation of a Continuous Variable, 462 // 7.3. Conditioning by Kriging, 465 // 7.4. Turning Bands, 472 // 7.5. Nonconditional Simulation of a Continuous Variable, 478 // 7.6. Nonconditional Simulation of an IRF-&, 506 // 7.7. Simulation of a Categorical Variable, 520 // 7.8. Object-Based Simulations: Boolean Models, 545 // 7.9. Constrained Simulations, 561 // 7.10. Practical Considerations, 571 // 7.11. Case Studies, 577 // 8. Scale Effects and Inverse Problems 593 // 8.1. Introduction, 593 8.2. Upscaling Permeability, 594 8.3. Stochastic Differential Equations, 602 8.4. Inverse Problem in Hydrogeology, 611 // Appendix 636 // References 650 // Index 687