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Geostatistics : Modeling Spatial Uncertainty



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Autore: Chil?s Jean-Paul Visualizza persona
Titolo: Geostatistics : Modeling Spatial Uncertainty Visualizza cluster
Pubblicazione: Hoboken, : Wiley, 2012
Edizione: 2nd ed.
Descrizione fisica: 1 online resource (740 p.)
Disciplina: 550
550.72
Soggetto topico: Earth sciences - Statistical methods
Earth sciences -- Statistical methods
Environmental engineering
Geology -- Statistical methods
Mining engineering
Geology
Earth & Environmental Sciences
Geology - General
Altri autori: DelfinerPierre  
Note generali: Description based upon print version of record.
Nota di contenuto: Geostatistics: 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
2.7: 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
4.3: 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
6.3: 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. Lantuéjoul); 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
7.5: 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
Sommario/riassunto: Praise 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
Titolo autorizzato: Geostatistics  Visualizza cluster
ISBN: 1-280-58852-7
9786613618351
1-118-13617-9
1-118-13618-7
1-118-13615-2
Formato: Materiale a stampa
Livello bibliografico Monografia
Lingua di pubblicazione: Inglese
Record Nr.: 9910808398903321
Lo trovi qui: Univ. Federico II
Opac: Controlla la disponibilità qui
Serie: Wiley Series in Probability and Statistics