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GSLIB: Geostatistical Software Library and User's Guide 2nd edition [Kõva köide]

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  • Formaat: Hardback, 384 pages, kaal: 700 g, numerous halftones, line figures and tables, + disk
  • Ilmumisaeg: 21-Aug-1997
  • Kirjastus: Oxford University Press Inc
  • ISBN-10: 0195100158
  • ISBN-13: 9780195100150
Teised raamatud teemal:
GSLIB: Geostatistical Software Library and User's Guide 2nd editionSuurem pilt
  • Formaat: Hardback, 384 pages, kaal: 700 g, numerous halftones, line figures and tables, + disk
  • Ilmumisaeg: 21-Aug-1997
  • Kirjastus: Oxford University Press Inc
  • ISBN-10: 0195100158
  • ISBN-13: 9780195100150
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780195100150.html
Märksõnad:
Geostatistics is the statistical study of phenomena that fluctuate in space and time. The original objective of the field was to improve forecasting for ore grades and reserves, but the mathematical generality of the approach has led to the application of geostatistics to other areas. GSLIB provides a source code that can be used as a starting point for custom program, advanced applications, and research. This new second edition is aimed at students, practitioners, and researchers who need powerful, flexible, and documented programs that are not confined to user-friendly menus. The book has been extensively revised and updated, and will include two MS-DOS disks, as in the First Edition. It offers the most advanced methods in the field, including co-kriging and conditional simulations, all developed in three-dimensions, and that can be run on any kind of computer. The package includes the GSLIB users guide and the programs on two disks.

Arvustused

Praise for the previous edition: "Provides concise theoretical discussions of relevant geostatistical concepts, with an emphasis on placing the provided routines in the context of current geostatistical practice. The text is loaded with citations and the resulting bibliography is a valuable resource within itself."--Kansas Geological Survey Praise for the first edition: "The authors (and programmers) should be applauded for this remarkable contribution to the research community."--Computers & Geosciences

I Introduction
3(6)
I.1 About the Source Code
6(3)
II Getting Started
9(34)
II.1 Geostatistical Concepts: A Review
9(11)
II.1.1 The Random Function Concept
11(1)
II.1.2 Inference and Stationarity
12(1)
II.1.3 Variogram
13(1)
II.1.4 Kriging
14(4)
II.1.5 Stochastic Simulation
18(2)
II.2 GSLIB Conventions
20(4)
II.2.1 Computer Requirements
20(1)
II.2.2 Data Files
21(1)
II.2.3 Grid Definition
22(1)
II.2.4 Program Execution and Parameter Files
23(1)
II.2.5 Machine Precision
24(1)
II.3 Variogram Model Specification
24(8)
II.3.1 A Straightforward 2D Example
29(1)
II.3.2 A 2D Example with Zonal Anisotropy
30(2)
II.4 Search Strategies
32(5)
II.5 Data Sets
37(3)
II.6 Problem Set One: Data Analysis
40(3)
III Variograms
43(20)
III.1 Measures of Spatial Variability
43(4)
III.2 GSLIB Variogram Programs
47(3)
III.3 Regularly Spaced Data gam
50(3)
III.4 Irregularly Spaced Data gamv
53(2)
III.5 Variogram Maps varmap
55(2)
III.6 Application Notes
57(5)
III.7 Problem Set Two: Variograms
62(1)
IV Kriging
63(56)
IV.1 Kriging with GSLIB
63(32)
IV.1.1 Simple Kriging
64(1)
IV.1.2 Ordinary Kriging
65(1)
IV.1.3 Kriging with a Trend Model
66(3)
IV.1.4 Kriging the Trend
69(1)
IV.1.5 Kriging with an External Drift
70(1)
IV.1.6 Factorial Kriging
71(2)
IV.1.7 Cokriging
73(2)
IV.1.8 Nonlinear Kriging
75(1)
IV.1.9 Indicator Kriging
76(10)
IV.1.10 Indicator Cokriging
86(1)
IV.1.11 Probability Kriging
87(1)
IV.1.12 Soft Kriging: The Markov-Bayes Model
88(4)
IV.1.13 Block Kriging
92(2)
IV.1.14 Cross Validation
94(1)
IV.2 A Straightforward 2D Kriging Program kb2d
95(1)
IV.3 A Flexible 3D Kriging Program kt3d
96(4)
IV.4 Cokriging Program cokb3d
100(3)
IV.5 Indicator Kriging Program ik3d
103(3)
IV.6 Application Notes
106(2)
IV.7 Problem Set Three: Kriging
108(7)
IV.8 Problem Set Four: Cokriging
115(1)
IV.9 Problem Set Five: Indicator Kriging
116(3)
V Simulation
119(80)
V.1 Principles of Stochastic Simulation
119(20)
V.1.1 Reproduction of Major Heterogeneities
122(1)
V.1.2 Joint Simulation of Several Variables
123(2)
V.1.3 The Sequential Simulation Approach
125(2)
V.1.4 Error Simulation
127(1)
V.1.5 Questions of Ergodicity
128(6)
V.1.6 Going Beyond a Discrete CDF
134(5)
V.2 Gaussian-Related Algorithms
139(10)
V.2.1 Normal Score Transform
141(1)
V.2.2 Checking for Bivariate Normality
142(2)
V.2.3 Sequential Gaussian Simulation
144(2)
V.2.4 LU Decomposition Algorithm
146(1)
V.2.5 The Turning Band Algorithm
147(1)
V.2.6 Multiple Truncations of a Gaussian Field
148(1)
V.3 Indicator-Based Algorithms
149(6)
V.3.1 Simulation of Categorical Variables
151(1)
V.3.2 Simulation of Continuous Variables
152(3)
V.4 p-Field Simulation
155(1)
V.5 Boolean Algorithms
156(2)
V.6 Simulated Annealing
158(11)
V.6.1 Simulation by Simulated Annealing
159(7)
V.6.2 Postprocessing with Simulated Annealing
166(1)
V.6.3 Iterative Simulation Techniques
167(2)
V.7 Gaussian Simulation Programs
169(6)
V.7.1 LU Simulation lusim
169(1)
V.7.2 Sequential Gaussian Simulation sgsim
170(4)
V.7.3 Multiple Truncations of a Gaussian Field gtsim
174(1)
V.8 Sequential Indicator Simulation Programs
175(7)
V.8.1 Indicator Simulation sisim
175(6)
V.8.2 p-Field Simulation pfsim
181(1)
V.9 A Boolean Simulation Program ellipsim
182(1)
V.10 Simulated Annealing Programs
183(6)
V.10.1 Simulated Annealing sasim
183(4)
V.10.2 An Annealing Postprocessor anneal
187(2)
V.11 Application Notes
189(2)
V.12 Problem Set Six: Simulation
191(8)
VI Other Useful Programs
199(42)
VI.1 PostScript Display
199(12)
VI.1.1 Location Maps locmap
201(1)
VI.1.2 Gray-and Color-Scale Maps pixelplt
202(2)
VI.1.3 Histograms and Statistics histplt
204(2)
VI.1.4 Normal Probability Plots probplt
206(1)
VI.1.5 Q-Q and P-P plots qpplt
207(1)
VI.1.6 Bivariate Scatterplots and Analysis scatplt
208(2)
VI.1.7 Smoothed Scatterplot Display bivplt
210(1)
VI.1.8 Variogram Plotting vargplt
211(1)
VI.2 Utility Programs
211(30)
VI.2.1 Coordinates addcoord and rotcoord
211(2)
VI.2.2 Cell Declustering declus
213(1)
VI.2.3 Histogram and Scattergram Smoothing
214(8)
VI.2.4 Random Drawing draw
222(1)
VI.2.5 Normal Score Transformation nscore
223(3)
VI.2.6 Normal Score Back Transformation backtr
226(1)
VI.2.7 General Transformation trans
227(3)
VI.2.8 Variogram Values from a Model vmodel
230(1)
VI.2.9 Gaussian Indicator Variograms bigaus
231(1)
VI.2.10 Library of Linear System Solvers
232(3)
VI.2.11 Bivariate Calibration bicalib
235(1)
VI.2.12 Postprocessing of IK Results postik
236(3)
VI.2.13 Postprocessing of Simulation Results postsim
239(2)
Appendices
241(106)
A Partial Solutions to Problem Sets
241(84)
A.1 Problem Set One: Data Analysis
241(12)
A.2 Problem Set Two: Variograms
253(13)
A.3 Problem Set Three: Kriging
266(5)
A.4 Problem Set Four: Cokriging
271(12)
A.5 Problem Set Five: Indicator Kriging
283(13)
A.6 Problem Set Six: Simulations
296(29)
B Software Installation
325(4)
B.1 Installation
325(2)
B.2 Troubleshooting
327(2)
C Programming Conventions
329(10)
C.1 General
329(1)
C.2 Dictionary of Variable Names
330(6)
C.3 Reference Lists of Parameter Codes
336(3)
D Alphabetical Listing of Programs
339(2)
E List of Acronyms and Notations
341(6)
E.1 Acronyms
341(1)
E.2 Common Notation
342(5)
Bibliography 347(16)
Index 363