Description |
xx, 249 pages : illustrations ; 24 cm |
Contents |
1. Introduction -- 2. Exploratory data analysis -- 3. Intrinsic model -- 4. Variogram fitting -- 5. Anisotropy -- 6. Variable mean -- 7. More linear estimation -- 8. Multiple variables -- 9. Estimation and GW models -- A. Probability theory review -- B. Lagrange multipliers -- C. Generation of realizations |
Summary |
Engineers and Applied Geophysicists Routinely encounter interpolation and estimation problems when analyzing data from field observations. Introduction to Geostatistics presents practical techniques for the estimation of spatial functions from sparse data. The author's unique approach is a synthesis of classic and geostatistical methods, with a focus on the most practical linear minimum-variance estimation methods, and includes suggestions on how to test and extend the applicability of such methods. Well illustrated with exercises and worked examples taken from hydrogeology, Introduction to Geostatistics assumes no background in statistics and is suitable for graduate-level courses in earth sciences, hydrology, and environmental engineering and also for self-study |
Notes |
Bibliography: p239-246. _ Includes index |
Bibliography |
Includes bibliographical references (pages 239-246) and index |
Notes |
Online version of the print title |
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Mode of access: World Wide Web |
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System requirements: Internet connectivity, World Wide Web browser, and Adobe Acrobat reader |
Subject |
Hydrogeology -- Statistical methods.
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Author |
Cambridge University Press.
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LC no. |
96028608 |
ISBN |
0521583128 (hc) |
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0521587476 (paperback) |
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