LEADER 05018nam 2200685Ia 450 001 9910808398903321 005 20200520144314.0 010 $a1-280-58852-7 010 $a9786613618351 010 $a1-118-13617-9 010 $a1-118-13618-7 010 $a1-118-13615-2 035 $a(CKB)2670000000148622 035 $a(EBL)693179 035 $a(SSID)ssj0000635789 035 $a(PQKBManifestationID)11437898 035 $a(PQKBTitleCode)TC0000635789 035 $a(PQKBWorkID)10653485 035 $a(PQKB)11281416 035 $a(MiAaPQ)EBC693179 035 $a(PPN)172062098 035 $a(OCoLC)779616853 035 $a(FR-PaCSA)88813008 035 $a(EXLCZ)992670000000148622 100 $a20120309d2012 uy 0 101 0 $aeng 135 $aur|n|---||||| 181 $ctxt 182 $cc 183 $acr 200 10$aGeostatistics $emodeling spatial uncertainty /$fJean-Paul Chiles, Pierre Delfiner 205 $a2nd ed. 210 $aHoboken, N.J. $cWiley$dc2012 215 $a1 online resource (740 p.) 225 1 $aWiley series in probability and statistics 300 $aDescription based upon print version of record. 311 $a0-470-18315-2 320 $aIncludes bibliographical references and index. 327 $aGeostatistics: Modeling Spatial Uncertainty; Contents; Preface to the Second Edition; Preface to the First Edition; Abbreviations; Introduction; Types of Problems Considered; Description or Interpretation?; 1. Preliminaries; 1.1: Random Functions; 1.2: On the Objectivity of Probabilistic Statements; 1.3: Transitive Theory; 2. Structural Analysis; 2.1: General Principles; 2.2: Variogram Cloud and Sample Variogram; 2.3: Mathematical Properties of the Variogram; 2.4: Regularization and Nugget Effect; 2.5: Variogram Models; 2.6: Fitting a Variogram Model 327 $a2.7: Variography in the Presence of a Drift2.8: Simple Applications of the Variogram; 2.9: Complements: Theory of Variogram Estimation and Fluctuation; 3. Kriging; 3.1: Introduction; 3.2: Notations and Assumptions; 3.3: Kriging with a Known Mean; 3.4: Kriging with an Unknown Mean; 3.5: Estimation of a Spatial Average; 3.6: Selection of a Kriging Neighborhood; 3.7: Measurement Errors and Outliers; 3.8: Case Study: The Channel Tunnel; 3.9: Kriging Under Inequality Constraints; 4. Intrinsic Model of Order k; 4.1: Introduction; 4.2: A Second Look at the Model of Universal Kriging 327 $a4.3: Allowable Linear Combinations of Order k4.4: Intrinsic Random Functions of Order k; 4.5: Generalized Covariance Functions; 4.6: Estimation in the IRF Model; 4.7: Generalized Variogram; 4.8: Automatic Structure Identification; 4.9: Stochastic Differential Equations; 5. Multivariate Methods; 5.1: Introduction; 5.2: Notations and Assumptions; 5.3: Simple Cokriging; 5.4: Universal Cokriging; 5.5: Derivative Information; 5.6: Multivariate Random Functions; 5.7: Shortcuts; 5.8: Space-Time Models; 6. Nonlinear Methods; 6.1: Introduction; 6.2: Global Point Distribution 327 $a6.3: Local Point Distribution: Simple Methods6.4: Local Estimation by Disjunctive Kriging; 6.5: Selectivity and Support Effect; 6.6: Multi-Gaussian Change-of-Support Model; 6.7: Affine Correction; 6.8: Discrete Gaussian Model; 6.9: Non-Gaussian Isofactorial Change-of-Support Models; 6.10: Applications and Discussion; 6.11: Change of Support by the Maximum (C. Lantue?joul); 7. Conditional Simulations; 7.1: Introduction and Definitions; 7.2: Direct Conditional Simulation of a Continuous Variable; 7.3: Conditioning by Kriging; 7.4: Turning Bands 327 $a7.5: Nonconditional Simulation of a Continuous Variable7.6: Simulation of a Categorical Variable; 7.7: Object-Based Simulations: Boolean Models; 7.8: Beyond Standard Conditioning; 7.9: Additional Topics; 7.10: Case Studies; Appendix; References; Index 330 $aPraise for the First Edition "". . . a readable, comprehensive volume that . . . belongs on the desk, close at hand, of any serious researcher or practitioner."" -Mathematical Geosciences The state of the art in geostatistics Geostatistical models and techniques such as kriging and stochastic multi-realizations exploit spatial correlations to evaluate natural resources, help optimize their development, and address environmental issues related to air and water quality, soil pollution, and forestry. Geostatistics: Modeling Spatial Uncertainty, Second Edition presents a comprehensive 410 0$aWiley series in probability and statistics. 606 $aEarth sciences$xStatistical methods 606 $aSpatial analysis (Statistics) 615 0$aEarth sciences$xStatistical methods. 615 0$aSpatial analysis (Statistics) 676 $a550 676 $a550.72 700 $aChiles$b Jean-Paul$0254038 701 $aDelfiner$b Pierre$0254039 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910808398903321 996 $aGeostatistics$967931 997 $aUNINA