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Modeling uncertainty in the earth sciences / Jef Caers

By: Resource type: Ressourcentyp: Buch (Online)Book (Online)Publisher number: EB00064687Language: English Publisher: Hoboken, N.J. : Wiley-Blackwell, 2011Description: 1 Online-Ressource (249 pages)ISBN:
  • 1119995922
  • 9781119995920
  • 1283177978
  • 9781283177979
  • 1119998719
  • 1119995930
  • 9781119998716
  • 9781119995937
  • 9781119992639
  • 111999263X
  • 9781119992622
  • 1119992621
  • 9781119992639
  • 9781119992622
Subject(s): Additional physical formats: 9781119992639 | Erscheint auch als: Modeling uncertainty in the earth sciences. Druck-Ausgabe 1. impr. Hoboken, N.J. : Wiley-Blackwell, 2011. XV, 229 S.DDC classification:
  • 550.15118
  • 551.01/5195
MSC: MSC: *86-01 | 86A32 | 00A71 | 00A79RVK: RVK: TG 1100LOC classification:
  • QE33.2.M3
DOI: DOI: 10.1002/9781119995920Online resources:
Contents:
Modeling Uncertainty inthe Earth Sciences; Contents; Preface; Acknowledgements; 1 Introduction; 1.1 Example Application; 1.1.1 Description; 1.1.2 3D Modeling; 1.2 Modeling Uncertainty; Further Reading; 2 Review on Statistical Analysis and Probability Theory; 2.1 Introduction; 2.2 Displaying Data with Graphs; 2.2.1 Histograms; 2.3 Describing Data with Numbers; 2.3.1 Measuring the Center; 2.3.2 Measuring the Spread; 2.3.3 Standard Deviation and Variance; 2.3.4 Properties of the Standard Deviation; 2.3.5 Quantiles and the QQ Plot; 2.4 Probability; 2.4.1 Introduction
2.4.2 Sample Space, Event, Outcomes2.4.3 Conditional Probability; 2.4.4 Bayes' Rule; 2.5 Random Variables; 2.5.1 Discrete Random Variables; 2.5.2 Continuous Random Variables; 2.5.2.1 Probability Density Function (pdf); 2.5.2.2 Cumulative Distribution Function; 2.5.3 Expectation and Variance; 2.5.3.1 Expectation; 2.5.3.2 Population Variance; 2.5.4 Examples of Distribution Functions; 2.5.4.1 The Gaussian (Normal) Random Variable and Distribution; 2.5.4.2 Bernoulli Random Variable; 2.5.4.3 Uniform Random Variable; 2.5.4.4 A Poisson Random Variable; 2.5.4.5 The Lognormal Distribution
2.5.5 The Empirical Distribution Function versus the Distribution Model2.5.6 Constructing a Distribution Function from Data; 2.5.7 Monte Carlo Simulation; 2.5.8 Data Transformations; 2.6 Bivariate Data Analysis; 2.6.1 Introduction; 2.6.2 Graphical Methods: Scatter plots; 2.6.3 Data Summary: Correlation (Coefficient); 2.6.3.1 Definition; 2.6.3.2 Properties of r; Further Reading; 3 Modeling Uncertainty: Concepts and Philosophies; 3.1 What is Uncertainty?; 3.2 Sources of Uncertainty; 3.3 Deterministic Modeling; 3.4 Models of Uncertainty; 3.5 Model and Data Relationship
3.6 Bayesian View on Uncertainty3.7 Model Verification and Falsification; 3.8 Model Complexity; 3.9 Talking about Uncertainty; 3.10 Examples; 3.10.1 Climate Modeling; 3.10.1.1 Description; 3.10.1.2 Creating Data Sets Using Models; 3.10.1.3 Parameterization of Subgrid Variability; 3.10.1.4 Model Complexity; 3.10.2 Reservoir Modeling; 3.10.2.1 Description; 3.10.2.2 Creating Data Sets Using Models; 3.10.2.3 Parameterization of Subgrid Variability; 3.10.2.4 Model Complexity; Further Reading; 4 Engineering the Earth: Making Decisions Under Uncertainty; 4.1 Introduction; 4.2 Making Decisions
4.2.1 Example Problem4.2.2 The Language of Decision Making; 4.2.3 Structuring the Decision; 4.2.4 Modeling the Decision; 4.2.4.1 Payoffs and Value Functions; 4.2.4.2 Weighting; 4.2.4.3 Trade-Offs; 4.2.4.4 Sensitivity Analysis; 4.3 Tools for Structuring Decision Problems; 4.3.1 Decision Trees; 4.3.2 Building Decision Trees; 4.3.3 Solving Decision Trees; 4.3.4 Sensitivity Analysis; Further Reading; 5 Modeling Spatial Continuity; 5.1 Introduction; 5.2 The Variogram; 5.2.1 Autocorrelation in 1D; 5.2.2 Autocorrelation in 2D and 3D; 5.2.3 The Variogram and Covariance Function
5.2.4 Variogram Analysis
Front MatterIntroduction -- Review on Statistical Analysis and Probability Theory -- Modeling Uncertainty: Concepts and Philosophies -- Engineering the Earth: Making Decisions Under Uncertainty -- Modeling Spatial Continuity -- Modeling Spatial Uncertainty -- Constraining Spatial Models of Uncertainty with Data -- Modeling Structural Uncertainty -- Visualizing Uncertainty -- Modeling Response Uncertainty -- Value of Information -- Example Case Study -- Index.
Summary: Front Matter -- Introduction -- Review on Statistical Analysis and Probability Theory -- Modeling Uncertainty: Concepts and Philosophies -- Engineering the Earth: Making Decisions Under Uncertainty -- Modeling Spatial Continuity -- Modeling Spatial Uncertainty -- Constraining Spatial Models of Uncertainty with Data -- Modeling Structural Uncertainty -- Visualizing Uncertainty -- Modeling Response Uncertainty -- Value of Information -- Example Case Study -- Index.Summary: Modeling Uncertainty in the Earth Sciences highlights the various issues, techniques and practical modeling tools available for modeling the uncertainty of complex Earth systems and the impact that it has on practical situations. The aim of the book is to provide an introductory overview which covers a broad range of tried-and-tested tools. Descriptions of concepts, philosophies, challenges, methodologies and workflows give the reader an understanding of the best way to make decisions under uncertainty for Earth Science problems. The book covers key issues such as: Spatial and time aspect; largPPN: PPN: 1679611585Package identifier: Produktsigel: ZDB-35-UBC | ZDB-35-WIC
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