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epub Geostatistics: Modeling Spatial Uncertainty download

by Jean-Paul Chilès,Pierre Delfiner

  • ISBN: 0470183152
  • Author: Jean-Paul Chilès,Pierre Delfiner
  • ePub ver: 1743 kb
  • Fb2 ver: 1743 kb
  • Rating: 4.4 of 5
  • Language: English
  • Pages: 734
  • Publisher: Wiley; 2 edition (March 26, 2012)
  • Formats: lrf lrf txt rtf
  • Category: Math
  • Subcategory: Mathematics
epub Geostatistics: Modeling Spatial Uncertainty download

Only 9 left in stock (more on the way). Computers &Geosciences, 1 February 2013). Jean-Paul Chilès is Deputy Director of the Center ofGeosciences and Geoengi?neering at MINES ParisTech, France. Pierre Delfiner is Principal of PetroDecisions, a consultingfirm based in Paris, France.

Geostatistics: Modeling Spatial Uncertainty by Jean-Paul Chiles; Pierre Delfiner. Geostatistics: Modeling Spatial Uncertainty by . P. January 2000 · Journal of the American Statistical Association. Chilès and P. Delfiner publishedin 1999 has been one of the most cited reference book in Geostatistics and spatialstatistics in the last decade

Jean-Paul Chilès is Deputy Director of the Center of Geosciences and Geoengi?neering at MINES ParisTech, France.

Jean-Paul Chilès is Deputy Director of the Center of Geosciences and Geoengi?neering at MINES ParisTech, France. Pierre Delfiner is Principal of PetroDecisions, a consulting firm based in Paris, France.

Geostatistics: Modeling Spatial Uncertainty, Jean-Paul Chilès, Pierre Delfiner.

Geostatistics: Modeling Spatial Uncertainty, Jean-Paul Chilès, Pierre Delfiner April 2013 · Computers & Geosciences. Any geostatistical prediction is built on a prior.

Geostatistics: Modeling Spatial Uncertainty is the only geostatistical book to address a broad audience in both industry and academia. An invaluable resource for geostatisticians, physicists, mining engineers, and earth science professionals such as petroleum geologists, geophysicists, and hydrogeologists, it is also an excellent supplementary text for graduate-level courses in related subjects. A novel, practical approach to modeling spatial uncertainty. This book deals with statistical models used to describe natural variables distributed in space or in time and space

Geostatistics: Modeling Spatial Uncertainty by . Delner published in 1999 has been one of the most cited reference book in Geostatistics and spatial statistics in the last decade.

Geostatistics: Modeling Spatial Uncertainty by . There are very good reasons for this: it is, in my opinion, the most comprehensive book on geostatistics, with an in-depth coverage of all as-pects, from random eld theory and spectral representation to virtually all practical issues arising when modeling spatial data, including variogram tting, (co) kriging, estimating nonlinear quantities in presence of a change of support, or when perform-ing

JEAN-PAUL CHILÈS BRGM and MINES ParisTech. PIERRE DELFINER PetroDecisions. Epistemology The quantification of spatial uncertainty requires a model specifying the mechanism by which spatial randomness is generated.

JEAN-PAUL CHILÈS BRGM and MINES ParisTech. 28 January 2012; 13:1:56. The simplest approach is to treat the regionalized variable as deterministic and the positions of the samples as random, assuming for example that they are selected uniformly and independently over a reference area, in which case standard statistical rules for independent random variables apply, such as that for the variance of the mean.

Geostatistics: Modeling Spatial Uncertainty Hardcover – 19 March 2012

Geostatistics: Modeling Spatial Uncertainty Hardcover – 19 March 2012. by Jean-Paul Chiles (Author), Pierre Delfiner (Author). Computers & Geosciences, 1 February 2013). Jean-Paul Chiles is Deputy Director of the Center of Geosciences and Geoengi?neering at MINES ParisTech, France.

Possibly due to the characteristic modesty of the author, two papers written by C. Lantuéjoul on this topic are not cited in the book. Chilès, P. Delfiner: Geostatistics: Modeling Spatial Uncertainty

Possibly due to the characteristic modesty of the author, two papers written by C. References are given below. Bacro JN, Bel L, Lantuéjoul C (2010) Testing the independence of maxima: from bivariate vectors to spatial extreme fields. Bel L, Bacro JN, Lantuéjoul C (2008) Assessing extremal dependence of environmental spatial fields. Environmetrics 19:163–182. Delfiner: Geostatistics: Modeling Spatial Uncertainty. Math Geosci 45, 377–380 (2013) doi:10.

Praise for the First Edition

". . . a readable, comprehensive volume that . . . belongs onthe desk, close at hand, of any serious researcher orpractitioner." —Mathematical Geosciences

The state of the art in geostatistics

Geostatistical models and techniques such as kriging andstochastic multi-realizations exploit spatial correlations toevaluate natural resources, help optimize their development, andaddress environmental issues related to air and water quality, soilpollution, and forestry. Geostatistics: Modeling SpatialUncertainty, Second Edition presents a comprehensive, up-to-datereference on the topic, now featuring the latest developments inthe field.

The authors explain both the theory and applications ofgeostatistics through a unified treatment that emphasizesmethodology. Key topics that are the foundation of geostatisticsare explored in-depth, including stationary and nonstationarymodels; linear and nonlinear methods; change of support;multivariate approaches; and conditional simulations. The SecondEdition highlights the growing number of applications ofgeostatistical methods and discusses three key areas of growth inthe field:

New results and methods, including kriging very large datasets;kriging with outliers; nonse??parable space-time covariances;multipoint simulations; pluri-gaussian simulations; gradualdeformation; and extreme value geostatistics

Newly formed connections between geostatistics and otherapproaches such as radial basis functions, Gaussian Markov randomfields, and data assimilation

New perspectives on topics such as collocated cokriging, krigingwith an external drift, discrete Gaussian change-of-support models,and simulation algorithms

Geostatistics, Second Edition is an excellent book for courseson the topic at the graduate level. It also serves as an invaluablereference for earth scientists, mining and petroleum engineers,geophysicists, and environmental statisticians who collect andanalyze data in their everyday work.

Comments (6)

Painshade
This is a comprehensive and definitive text on geostatistics. Although the more theoretical sections are marked as optional, be warned that it is not for the feint-hearted. However, the cases are very worthwhile, the coverage and depth is very good and the mathematical rigour is evident. The discussions of applications is good (in my view) and the explanations mostly lucid. In the traditions of the French school, much mathematics is presumed to be evident or obvious, when for us mortals it is actually hard work. But this book rewards the diligent reader. For the professional Geostatistician or serious student it is a mandatory text.
SkroN
More than the average text on Geostats - highly recommended for those with some math background in random functions.
Yadon
Probably the best book in Geostatistics. I cannot recommend it more highly.
Includes multipoint simulations, pluri-gaussian simulations,gradual deformation etc
Superb!
Umi
There are a large number of books on geostatistics, usually introductory books dealing with parts of the subject. The volume by Chiles and Delfiner is THE comprehensive reference book in geostatistics that has been missing up to now.
It covers every part of geostatistics. After a useful introduction and preliminaries, different chapters are devoted successively to structural analysis, kriging, the intrinsic model of order k, multivariate methods, nonlinear methods, conditional simulations, scale effects and inverse problems.
Within each section, the book offers an accurate perspective of the different geostatistical methods. Practical approaches as well as theoretical developments are jointly considered, providing a sound basis to the user.
The writing is fluent, with an extensive documentation and a most helpful index.
The book will benefit those who want to know more about a specific method, as well as those who are looking for different approaches to a given problem. It will be valuable for academics and students, as well as scientists, engineers and practitioners from different domains such as mining, hydrogeology, oil exploration, soil science, forestry, and environmental sciences.
Purebinder
Highly recommended! This is easily the most comprehensive, scholarly, and up-to-date work in the area.
The authors cover the entire range of geostatistics - structural analysis (variogram fitting), kriging, multivariate and nonlinear methods, conditional simulation, scale effects, and inverse problems. The chapter on geostatistical simulation is particularly impressive, and much unpublished work of Georges Matheron and the Center for Geostatistics at Fontainebleau, France, is made available here for the first time. Practical and theoretical aspects of geostatistics balance each other very nicely.
This is not an introductory text - there are other books in the area which are custom-tailored to beginners - but it is an invaluable, and very carefully written, reference. For anyone applying geostatistical techniques in environmental sciences, earth sciences, engineering, or related fields, this book is a must-have!
Kabandis
I found this book a little bit cheaper than the regular prize. When I got it I noticed the printing and paper quality are lower than the older books. Anyway, it is a good reference for conventional Geostatistics.

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