Collecting Spatial Data: Optimum Design of Experiments for Random Fields (Contributions to Statistics) |  | Creator: W. G. Muller
Publisher: Physica-Verlag
Category: Book
Buy Used: $56.00
Rating:  1 reviews
Sales Rank: 6349049
Media: Paperback
Pages: 186
Number Of Items: 1
Shipping Weight (lbs): 0.7
Dimensions (in): 9.3 x 6.3 x 0.5
ISBN: 3790811343
Dewey Decimal Number: 001.434
EAN: 9783790811346
Publication Date: November 1998
Availability: Usually ships in 1-2 business days
Shipping: International shipping available
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| Editorial Reviews:
Product Description
The book is concerned with the statistical theory for locating spatial sensors. It bridges the gap between spatial statistics and optimum design theory. After introductions to those two fields the topics of exploratory designs and designs for spatial trend and variogram estimation are treated. A new methodology, so-called approximate information matrices, are employed to cope with the problem of correlated observations. A great number of relevant references are collected and put into a common perspective. The theoretical investigations are accompanied by a practical example, the redesign of an Upper-Austrian air pollution monitoring network. The reader will find respective theory and recommendations on how to efficiently plan a specific purpose spatial monitoring network.
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| Customer Reviews:
First book on spatial design April 5, 2001
DataGuru (DC)
4 out of 5 found this review helpful
Spatial statistics is an important subject, and there are excellent books such as Ripley, Cressie's books. However, very little work has been done on how to collect spatial data, though experimental design is an old but important subject in Statistics. This book, now in its second edition, makes an excellent start in this emerging area. This reviewer, fortunately, has the chance to participate in a multinational weather experiment in which one of the goals is to collect additional spatial data for improving existing data network and for improving short-time-scale and mesoscale weather forecast. This led to our study of adaptive design for spatial dynamical systems and spatial fields, leading to a 1999 paper on J. of Atmospheric Sciences and a book Chapter in Studies in Atmospheric Sciences published by Springer in 2000. Now, adaptive spatial design, or targeted observations, is an very hot area in meteorology, and many papers have published in meteorology dealing with various aspects of applications. There are good economic reasons also for doing adaptive design, though practical impacts of this approach need to be justified also. After making this unnecessary detour, what do I think of this book? Well, I think it's an excellent supplementary book for a spatial statistics course. This book only covers the classic aspects of spatial design, namely a frequentist approach to static design for standard spatial estimation and prediction, with applications such as in designing monitoring stations. By combining with our more recent work optimal design using Bayesian methods, you probably get a very good coverage of statistical design for spatial or space-time fields, an area which I foresee more developments in the future.
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