000 02628nam a22003498i 4500
001 CR9780511626166
003 UkCbUP
005 20220711202545.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 141103s1997||||enk o ||1 0|eng|d
020 _a9780511626166 (ebook)
020 _z9780521583121 (hardback)
020 _z9780521587471 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aGB1001.72.S7
_bK57 1997
082 0 0 _a551.49/072
_220
100 1 _aKitanidis, P. K.
_q(Peter K.),
_eauthor.
_94605
245 1 0 _aIntroduction to geostatistics :
_bapplications to hydrogeology /
_cP.K. Kitanidis.
264 1 _aCambridge :
_bCambridge University Press,
_c1997.
300 _a1 online resource (xx, 249 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
500 _aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
505 0 _a1. 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.
520 _aEngineers and applied geophysicists routinely encounter interpolation and estimation problems when analysing 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. The author includes many useful methods (often not covered in other geostatistics books) such as estimating variogram parameters, evaluating the need for a variable mean, parameter estimation and model testing in complex cases (e.g. anisotropy, variable mean, and multiple variables), and using information from deterministic mathematical models. 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.
650 0 _aHydrogeology
_xStatistical methods.
_94606
776 0 8 _iPrint version:
_z9780521583121
856 4 0 _uhttps://doi.org/10.1017/CBO9780511626166
942 _cEBK
999 _c68304
_d68304