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by: Michael L. Stein  List Price: $89.95 Amazon.com's Price: $63.96 You Save: $25.99 (29%)Prices subject to change. Availability: Usually ships in 24 hours
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Binding: HardcoverDewey Decimal Number: 622.1015195 EAN: 9780387986296 Edition: 1 ISBN: 0387986294 Label: Springer Manufacturer: Springer Number Of Items: 1 Number Of Pages: 247 Publication Date: June 22, 1999 Publisher: Springer Studio: Springer Accessories:
Browse for similar items by category: Click to Display Editorial Review: Product Description: Prediction of a random field based on observations of the random field at some set of locations arises in mining, hydrology, atmospheric sciences, and geography. Kriging, a prediction scheme defined as any prediction scheme that minimizes mean squared prediction error among some class of predictors under a particular model for the field, is commonly used in all these areas of prediction. This book summarizes past work and describes new approaches to thinking about kriging. Average Rating:
 Rating:  - great theoretical treatment of spatial data analysis and krigingMichael Stein got his Ph.D. in Statistics from Stanford University under the direction of Paul Switzer. I also studied at Stanford years earlier and also learned about kriging from Switzer. Kriging is a very popular technique for interpolation of spatial data between measurement points. It is an optimal linear technique when the spatial covariance structure is known. It has many practical applications to pollution data, geological data etc. Stein develops the theory as far as he can for the case ... Read More Rating:  - A good bookSeveral chapters are not easy to read because of the material, also is not comprehensive about kriging; but despite that, it has a lot of interesting results and it is worth of reading. Rating: - first theoretical treatment of kriging with estimated cov.Michael Stein got his Ph.D. in Statistics from Stanford University under the direction of Paul Switzer. I also studied at Stanford years earlier and also learned about kriging from Switzer. Kriging is a very popular technique for interpolation of spatial data between measurement points. It is an optimal linear technique when the spatial covariance structure is known. It has many practical applications to pollution data, geological data etc. Stein develops the theory as far as he can for the ... Read More 
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