Handbook of Mathematical Geosciences
-15%
portes grátis
Handbook of Mathematical Geosciences
Fifty Years of IAMG
Cheng, Qiuming; Daya Sagar, B.S.; Agterberg, Frits
Springer International Publishing AG
07/2018
914
Dura
Inglês
9783319789989
15 a 20 dias
Descrição não disponível.
1. Forward.- 2. Preface.- 3. Introduction.- 4. Part I. Chapter 1 Kriging, Splines, Conditional Simulation, Bayesian In-version and Ensemble Kalman Filtering.- 5. Chapter 2 A Statistical Commentary on Mineral Prospectivity analysis.- 6. Chapter 3 Testing joint conditional independence of categorical random variables with a standard log-likelihood ratio test.- 7. Chapter 4 Modelling Compositional Data. The Sample Space Approach.- 8. Chapter 5 Properties of Sums of Geological Random Variables.- 9. Chapter 6 A Statistical Analysis of the Jacobian in Retrievals of Satellite Data.- 10. Chapter 7 All Realizations All the Time.- 11. Chapter 8 Binary Coefficients Redux.- 12. Chapter 9 Tracking Plurigaussian Simulations.- 13. Chapter 10 Mathematical Geosciences: Local Singularity Analysis of Nonlinear Earth Processes and Extreme Geo-Events.- 14. Chapter 11 Electrofacies in Reservoir Characterization.- 15. Chapter 12 Forecast of Shoreline Variations by Means of Median Sets.- 16. Chapter 13 An Introduction to the Spatio-Temporal Analysis of Sat-ellite Remote Sensing Data for Geostatisticians.- 17. Chapter 14 Flint drinking water crisis: a first attempt to model geo-statistically the space-time distribution of water lead levels.- 18. Chapter 15 Statistical Parametric Mapping for Geoscience Applications.- 19. Chapter 16 Water chemistry: are new challenges possible from CoDA (Compositional Data Analysis) point of view?.- 20. Chapter 17 Analysis of the United States Portion of the North American Soil Geochemical Landscapes Project - A Compositional Framework Approach.- 21. Chapter 18 Quantifying the Impacts of Uncertainty.- 22. Chapter 19. Advances in Sensitivity Analysis of Uncertainty due to Sampling Density for Spatially Correlated Attributes.- 23. Chapter 20 Predicting Molybdenum Deposit Growth.- 24. Chapter 21 General Framework of Quantitative Target Selections.- 25. Chapter 22 Solving the Wrong Resource Assessment Problems Precisely.- 26. Chapter 23 two ideas for analysis of multivariate geochemical survey data: proximity regression and principal component residuals.- 27. Chapter 24 Mathematical minerals: A history of petrophysical petrography.- 28. Chapter 25 Geostatistics for Seismic Characterization of Oil Reservoirs.- 29. Chapter 26 Statistical Modeling of Regional and Worldwide Size-Frequency Distributions of Metal Deposits.- 30. Chapter 27 Bayesianism in the Geosciences.- 31.Chapter 28 Geological Objects and Physical Parameter Fields in the Subsurface: A Review.- 32.Chapter 29 Fifty Years of Kriging.- 33. Chapter 30 Multiple Point Statistics: A Review.- 34. Chapter 31 When Should We Use Multiple-Point Geostatistics?.- 35. Chapter 32 The Origins of the Multiple-Point Statistics (MPS) Algorithm.- 36. Chapter 33 Predictive Geometallurgy: An Interdisciplinary Key Challenge for Mathematical Geosciences?.- 37. Chapter 34 Data Science for Geoscience: Leveraging Mathematical Geosciences with Semantics and Open Data.- 38. Chapter 35 Mathematical Morphology in Geosciences and GISci: An Illustrative Review.- 39. Chapter 36 IAMG: Recollections from the Early Years.- 40. Chapter 37 Forward and Inverse Models over 70 Years.- 41. Chapter 38 From individual personal contacts 1962-1968 to my 50 years of service.- 42. Chapter 39 Andrey Borisovich Vistelius.- 43. Chapter 40 Fifty Years' Experience with Hidden Errors in Applying Classic Mathematical Geology.- 44. Chapter 41 Mathematical Geology by Example: Teaching and Learning Perspectives.
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Mathematical Geosciences handbook;Geoinformatics;Geocomputations;Geostatistics and Simulation;Geoprediction;IAMG anniversary;IAMG award winning geoscientists;fractals and mathematical geoscience;Open access;quantitative geology
1. Forward.- 2. Preface.- 3. Introduction.- 4. Part I. Chapter 1 Kriging, Splines, Conditional Simulation, Bayesian In-version and Ensemble Kalman Filtering.- 5. Chapter 2 A Statistical Commentary on Mineral Prospectivity analysis.- 6. Chapter 3 Testing joint conditional independence of categorical random variables with a standard log-likelihood ratio test.- 7. Chapter 4 Modelling Compositional Data. The Sample Space Approach.- 8. Chapter 5 Properties of Sums of Geological Random Variables.- 9. Chapter 6 A Statistical Analysis of the Jacobian in Retrievals of Satellite Data.- 10. Chapter 7 All Realizations All the Time.- 11. Chapter 8 Binary Coefficients Redux.- 12. Chapter 9 Tracking Plurigaussian Simulations.- 13. Chapter 10 Mathematical Geosciences: Local Singularity Analysis of Nonlinear Earth Processes and Extreme Geo-Events.- 14. Chapter 11 Electrofacies in Reservoir Characterization.- 15. Chapter 12 Forecast of Shoreline Variations by Means of Median Sets.- 16. Chapter 13 An Introduction to the Spatio-Temporal Analysis of Sat-ellite Remote Sensing Data for Geostatisticians.- 17. Chapter 14 Flint drinking water crisis: a first attempt to model geo-statistically the space-time distribution of water lead levels.- 18. Chapter 15 Statistical Parametric Mapping for Geoscience Applications.- 19. Chapter 16 Water chemistry: are new challenges possible from CoDA (Compositional Data Analysis) point of view?.- 20. Chapter 17 Analysis of the United States Portion of the North American Soil Geochemical Landscapes Project - A Compositional Framework Approach.- 21. Chapter 18 Quantifying the Impacts of Uncertainty.- 22. Chapter 19. Advances in Sensitivity Analysis of Uncertainty due to Sampling Density for Spatially Correlated Attributes.- 23. Chapter 20 Predicting Molybdenum Deposit Growth.- 24. Chapter 21 General Framework of Quantitative Target Selections.- 25. Chapter 22 Solving the Wrong Resource Assessment Problems Precisely.- 26. Chapter 23 two ideas for analysis of multivariate geochemical survey data: proximity regression and principal component residuals.- 27. Chapter 24 Mathematical minerals: A history of petrophysical petrography.- 28. Chapter 25 Geostatistics for Seismic Characterization of Oil Reservoirs.- 29. Chapter 26 Statistical Modeling of Regional and Worldwide Size-Frequency Distributions of Metal Deposits.- 30. Chapter 27 Bayesianism in the Geosciences.- 31.Chapter 28 Geological Objects and Physical Parameter Fields in the Subsurface: A Review.- 32.Chapter 29 Fifty Years of Kriging.- 33. Chapter 30 Multiple Point Statistics: A Review.- 34. Chapter 31 When Should We Use Multiple-Point Geostatistics?.- 35. Chapter 32 The Origins of the Multiple-Point Statistics (MPS) Algorithm.- 36. Chapter 33 Predictive Geometallurgy: An Interdisciplinary Key Challenge for Mathematical Geosciences?.- 37. Chapter 34 Data Science for Geoscience: Leveraging Mathematical Geosciences with Semantics and Open Data.- 38. Chapter 35 Mathematical Morphology in Geosciences and GISci: An Illustrative Review.- 39. Chapter 36 IAMG: Recollections from the Early Years.- 40. Chapter 37 Forward and Inverse Models over 70 Years.- 41. Chapter 38 From individual personal contacts 1962-1968 to my 50 years of service.- 42. Chapter 39 Andrey Borisovich Vistelius.- 43. Chapter 40 Fifty Years' Experience with Hidden Errors in Applying Classic Mathematical Geology.- 44. Chapter 41 Mathematical Geology by Example: Teaching and Learning Perspectives.
Este título pertence ao(s) assunto(s) indicados(s). Para ver outros títulos clique no assunto desejado.
