Collecting Spatial Data: Optimum Design of Experiments for Random Fields

Werner G. Müller

ISBN 10: 3540311742 / ISBN 13: 9783540311744

Published by Springer Verlag, 2007

About this Item

3rd revised edition. 242 pages. 9.50x6.25x0.75 inches. In Stock.

Seller Inventory # x-3540311742

Bibliographic Details

• Title: Collecting Spatial Data: Optimum Design of Experiments for Random Fields
• Publisher: Springer Verlag
• Publication Date: 2007
• Language: English
• ISBN 10: 3540311742
• ISBN 13: 9783540311744
• Binding: Hardcover
• Edition: 3rd Edition
• Condition: Brand New
• Weight: 0.5 kilograms

About this title

Synopsis

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. Special attention is devoted to describing new methodologies to cope with the problem of correlated observations.

From the Back Cover

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. Special attention is devoted to describing new methodologies 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. A reader should be able to find respective theory and recommendations on how to efficiently plan a specific purpose spatial monitoring network. The third edition takes into account the rapid development in the area of spatial statistics by including new relevant research and references. The revised edition contains additional material on design for detecting spatial dependence and for estimating parametrized covariance functions.