MARC details
| 000 -LEADER |
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| fixed length control field |
07306cam a22003738i 4500 |
| 001 - CONTROL NUMBER |
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| control field |
18649784 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
OSt |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20170228160709.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
150608s2015 enk b 001 0 eng |
| 010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
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| LC control number |
2015022572 |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9781107040267 (hbk.) |
| 040 ## - CATALOGING SOURCE |
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| Original cataloging agency |
Indian Institute for Human Settlements-Bangalore |
| Language of cataloging |
eng |
| Transcribing agency |
DLC |
| Description conventions |
rda |
| Modifying agency |
IIHS |
| 042 ## - AUTHENTICATION CODE |
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| Authentication code |
pcc |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
550.01156 EID |
| Edition number |
23 |
| Item number |
009925 |
| 100 1# - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Eidsvik, Jo. |
| 245 10 - TITLE STATEMENT |
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| Title |
Value of information in the earth sciences : |
| Remainder of title |
integrating spatial modeling and decision analysis / |
| Statement of responsibility, etc |
Jo Eidsvik, Tapan Mukerji, and Debarun Bhattacharjya. |
| 264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
Cambridge : |
| Name of producer, publisher, distributor, manufacturer |
Cambridge University Press, |
| Date of production, publication, distribution, manufacture, or copyright notice |
2015. |
| 300 ## - PHYSICAL DESCRIPTION |
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| Extent |
xiii, 385 pages : |
| Other physical details |
illustrations (black and white) ; |
| Dimensions |
26 cm |
| 336 ## - Content type term (R) |
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| Content type term (R) |
text |
| Source (NR) |
rdacontent |
| 337 ## - Media Type (R) |
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| Media type term (R) |
unmediated |
| Source (NR) |
rdamedia |
| 338 ## - Carrier Type (R) |
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| Carrier type term (R) |
volume |
| Source (NR) |
rdacarrier |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
Machine generated contents note: 1.Introduction<br/>1.1.What is the value of information?<br/>1.2.Motivating examples from the Earth sciences<br/>1.3.Contributions of this book<br/>1.4.Organization<br/>1.5.Intended audience and prerequisites<br/>1.6.Bibliographic notes<br/>2.Statistical models and methods<br/>2.1.Uncertainty quantification, information gathering, and data examples<br/>2.2.Notation and probability models<br/>2.2.1.Univariate probability distributions<br/>2.2.2.Multivariate probability distributions<br/>2.3.Conditional probability, graphical models, and Bayes' rule<br/>2.3.1.Conditional probability<br/>2.3.2.Graphical models<br/>2.3.3.Bayesian updating from data<br/>2.3.4.Examples<br/>2.4.Inference of model parameters<br/>2.4.1.Maximum likelihood estimation<br/>2.4.2.Examples<br/>2.5.Monte Carlo methods and other approximation techniques<br/>2.5.1.Analysis by simulation<br/>2.5.2.Solving integrals<br/>2.5.3.Sampling methods<br/>2.5.4.Example<br/>2.6.Bibliographic notes<br/>Contents note continued: 3.Decision analysis<br/>3.1.Background<br/>3.2.Decision situations: terminology and notation<br/>3.2.1.Decisions, uncertainties, and values<br/>3.2.2.Utilities and certain equivalent<br/>3.2.3.Maximizing expected utility<br/>3.2.4.Examples<br/>3.3.Graphical models<br/>3.3.1.Decision trees<br/>3.3.2.Influence diagrams<br/>3.3.3.Examples<br/>3.4.Value of information<br/>3.4.1.Definition<br/>3.4.2.Perfect versus imperfect information<br/>3.4.3.Relevant, material, and economic information<br/>3.4.4.Examples<br/>3.5.Bibliographic notes<br/>4.Spatial modeling<br/>4.1.Goals of stochastic modeling of spatial processes<br/>4.2.Random fields, variograms, and covariance<br/>4.3.Prediction and simulation<br/>4.3.1.Spatial prediction and Kriging<br/>4.3.2.Common geostatistical stochastic simulation methods<br/>4.4.Gaussian models<br/>4.4.1.The spatial regression model<br/>4.4.2.Optimal spatial prediction: Kriging<br/>4.4.3.Multivariate hierarchical spatial regression model<br/>4.4.4.Examples<br/>Contents note continued: 4.5.Non-Gaussian response models and hierarchical spatial models<br/>4.5.1.Skew-normal models<br/>4.5.2.Spatial generalized linear models<br/>4.5.3.Example<br/>4.6.Categorical spatial models<br/>4.6.1.Indicator random variables<br/>4.6.2.Truncated Gaussian and pluri-Gaussian models<br/>4.6.3.Categorical Markov random field models<br/>4.6.4.Example<br/>4.7.Multiple-point geostatistics<br/>4.7.1.Algorithms<br/>4.7.2.Example<br/>4.8.Bibliographic notes<br/>5.Value of information in spatial decision situations<br/>5.1.Introduction<br/>5.1.1.Spatial decision situations<br/>5.1.2.Information gathering in spatial decision situations<br/>5.1.3.Overview of models<br/>5.2.Value of information: a formulation for static models<br/>5.2.1.Prior value<br/>5.2.2.Posterior value<br/>5.2.3.Special cases: an overview<br/>5.3.Special case: low decision flexibility and decoupled value<br/>5.3.1.Prior value<br/>5.3.2.Posterior value<br/>5.3.3.Computational notes<br/>5.3.4.Example<br/>Contents note continued: 5.4.Special case: high decision flexibility and decoupled value<br/>5.4.1.Prior value<br/>5.4.2.Posterior value<br/>5.4.3.Computational notes<br/>5.4.4.Examples<br/>5.5.Special case: low decision flexibility and coupled value<br/>5.5.1.Prior value<br/>5.5.2.Posterior value<br/>5.5.3.Computational notes<br/>5.5.4.Example<br/>5.6.Special case: high decision flexibility and coupled value<br/>5.6.1.Prior value<br/>5.6.2.Posterior value<br/>5.6.3.Computational notes<br/>5.6.4.Example<br/>5.7.More complex decision situations<br/>5.7.1.Generalized risk preferences<br/>5.7.2.Additional constraints<br/>5.7.3.Sequential decision situations<br/>5.8.Sequential information gathering<br/>5.9.Other information measures<br/>5.9.1.Entropy<br/>5.9.2.Prediction variance<br/>5.9.3.Prediction error<br/>5.10.Bibliographic notes<br/>6.Earth sciences applications<br/>6.1.Workflow<br/>6.2.Exploration of petroleum prospects<br/>6.2.1.Gotta get myself connected: Bayesian network example<br/>Contents note continued: 6.2.2.Basin street blues: basin modeling example<br/>6.2.3.Risky business: petroleum prospect risking example<br/>6.3.Reservoir characterization from geophysical data<br/>6.3.1.Black gold in a white plight: reservior characterization example<br/>6.3.2.Reservoir dogs: seismic and electromagnetic data example<br/>6.4.Mine planning and safety<br/>6.4.1.I love rock and ore: mining oxide grade example<br/>6.4.2.We will rock you: rock hazard example<br/>6.5.Groundwater management<br/>6.5.1.Salt water wells in my eyes: groundwater management example<br/>6.6.Bibliographic notes<br/>7.Problems and projects<br/>7.1.Problem and tutorial hands-on projects<br/>7.1.1.Problem sets<br/>7.1.2.Hands-on projects<br/>7.2.Hands on: exploration of petroleum prospects<br/>7.2.1.Gotta get myself connected: Bayesian network example<br/>7.2.2.Basin street blues: basin modeling example<br/>7.2.3.Risky business: petroleum prospect risking example<br/>Contents note continued: 7.3.Hands on: reservoir characterization from geophysical data<br/>7.3.1.Black gold in a white plight: reservoir characterization example<br/>7.3.2.Reservoir dogs: seismic and electromagnetic data example<br/>7.4.Hands on: mine planning and safety<br/>7.4.1.I love rock and ore: mining oxide grade example<br/>7.4.2.We will rock you: rock hazard example<br/>7.5.Hands on: groundwater management<br/>7.5.1.Part I: salt water wells in my eyes<br/>groundwater monitoring in Netica<br/>7.5.2.Part II: salt water wells in my eyes<br/>groundwater monitoring in BNT<br/>Appendix: selected statistical models and sampling methods<br/>Appendix A.1 Gaussian distribution<br/>A.1.1.Definition and properties<br/>A.1.2.Decision analysis and VOI results<br/>Appendix A.2 Generalized linear models<br/>A.2.1.Definition and properties<br/>A.2.2.Decision analysis and VOI results<br/>Appendix A.3 Markov chains and hidden Markov models<br/>A.3.1.Definition and properties<br/>Contents note continued: A.3.2.Decision analysis and VOI results<br/>Appendix A.4 Categorical Markov random fields<br/>A.4.1.Definition and properties<br/>A.4.2.Decision analysis and VOI results<br/>Appendix A.5 Discrete graphs and Bayesian networks<br/>A.5.1.Definition and properties<br/>A.5.2.Decision analysis and VOI results<br/>Appendix B Sampling methods. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
Presents a unified framework for assessing the value of potential data gathering schemes, with a focus on the Earth sciences. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Earth sciences |
| General subdivision |
Information services. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Geochemical prospecting. |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
|---|
| Topical term or geographic name as entry element |
Communication in science. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
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| Personal name |
Mukerji, Tapan. |
| 700 1# - ADDED ENTRY--PERSONAL NAME |
|---|
| Personal name |
Bhattacharjya, Debarun. |
| 856 42 - ELECTRONIC LOCATION AND ACCESS |
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| Materials specified |
Table of contents |
| Uniform Resource Identifier |
<a href="http://www.openisbn.com/isbn/1107040264/">http://www.openisbn.com/isbn/1107040264/</a> |
| 906 ## - LOCAL DATA ELEMENT F, LDF (RLIN) |
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| a |
7 |
| b |
cbc |
| c |
orignew |
| d |
1 |
| e |
ecip |
| f |
20 |
| g |
y-gencatlg |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
Dewey Decimal Classification |
| Koha item type |
Book |
