Book Title: Collecting Spatial Data (2nd Ed)
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. A reader should be able to find respective theory and recommendations on how to efficiently plan a specific purpose spatial monitoring network. The revised edition contains additional material and exercises. Keywords: Environmental Monitoring, Experimental Design, R?umliche Daten, R?umliche Statistik, Spatial Data, Spatial Statistics, Umweltmonitoring, Umweltmonotoring, Versuchsplanung Contents: Introduction.- Fundamentals of Spatial Statistics.- Estimation of Spatial Trend. Universal Kriging. Local Regression. Variogram Fitting. Example. Exercises. References.- Fundamentals of Experimental Design.- Information Matrices. Design Criteria. Numerical Algorithms. Further Design Topics Useful in the Spatial Setting. Example. Exercises. References.- Exploratory Designs.- Deterministic and Random Sampling. Space Filling Designs. Designs for Local Regression. Model Discriminating Designs. Example. Exercises. References.- Designs for Spatial Trend Estimation.- Approximate Information Matrices. Replication-Free Designs. Designs for Correlated Fields. Designs for Spatial Prediction. Example. Exercises. References.- Multipurpose Designs Including Designs for Variogram Fitting.- Designs for Variogram Estimation. Augmenting Designs. Alternative Methods which Ignore Correlations. Combining Different Purpose Designs. Example. Exercises. References.- Appendix.- Data Sets. Proofs for Chapter 2. Proofs for Chapter 3. Proofs for Chapter 4. Proofs for Chapter 5. Proofs for Chapter 6. D2PT Description. References.- List of Figures.- Author Index.- Subject Index. | ||||||||

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Book Title: Collecting Spatial Data (2nd Ed)
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< < | Book Author(s): Werner G. M?ller | |||||||

> > | Book Author(s): Werner G. Müller | |||||||

Book Publisher: Springer Verlag | ||||||||

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> > | Date of Publication: 1 October 2000 | |||||||

Cost: 100 US$
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. A reader should be able to find respective theory and recommendations on how to efficiently plan a specific purpose spatial monitoring network. The revised edition contains additional material and exercises. Keywords: Environmental Monitoring, Experimental Design, R?umliche Daten, R?umliche Statistik, Spatial Data, Spatial Statistics, Umweltmonitoring, Umweltmonotoring, Versuchsplanung | ||||||||

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< < | Contents: Introduction.- Fundamentals of Spatial Statistics.- Estimation of Spatial Trend. Universal Kriging. Local Regression. Variogram Fitting. Example. Exercises. References.- Fundamentals of Experimental Design.- Information Matrices. Design Criteria. Numerical Algorithms. Further Design Topics Useful in the Spatial Setting. Example. Exercises. References.- Exploratory Designs.- Deterministic and Random Sampling. Space Filling Designs. Designs for Local Regression. Model Discriminating Designs. Example. Exercises. References.- Designs for Spatial Trend Estimation.- Approximate Information Matrices. Replication-Free Designs. Designs for Correlated Fields. Designs for Spatial Prediction. Example. Exercises. References.- Multipurpose Designs Including Designs for Variogram Fitting.- Designs for Variogram Estimation. Augmenting Designs. Alternative Methods which Ignore Correlations. Combining Different Purpose Designs. Example. Exercises. References.- Appendix.- Data Sets. Proofs for Chapter 2. Proofs for Chapter 3. Proofs for Chapter 4. Proofs for Chapter 5. Proofs for Chapter 6. D2PT Description. References.- List of Figures.- Author Index.- Subject Index. | |||||||

> > | Contents: Introduction.- Fundamentals of Spatial Statistics.- Estimation of Spatial Trend. Universal Kriging. Local Regression. Variogram Fitting. Example. Exercises. References.- Fundamentals of Experimental Design.- Information Matrices. Design Criteria. Numerical Algorithms. Further Design Topics Useful in the Spatial Setting. Example. Exercises. References.- Exploratory Designs.- Deterministic and Random Sampling. Space Filling Designs. Designs for Local Regression. Model Discriminating Designs. Example. Exercises. References.- Designs for Spatial Trend Estimation.- Approximate Information Matrices. Replication-Free Designs. Designs for Correlated Fields. Designs for Spatial Prediction. Example. Exercises. References.- Multipurpose Designs Including Designs for Variogram Fitting.- Designs for Variogram Estimation. Augmenting Designs. Alternative Methods which Ignore Correlations. Combining Different Purpose Designs. Example. Exercises. References.- Appendix.- Data Sets. Proofs for Chapter 2. Proofs for Chapter 3. Proofs for Chapter 4. Proofs for Chapter 5. Proofs for Chapter 6. D2PT Description. References.- List of Figures.- Author Index.- Subject Index. | |||||||

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Book Title: Collecting Spatial Data (2nd Ed)
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. A reader should be able to find respective theory and recommendations on how to efficiently plan a specific purpose spatial monitoring network. The revised edition contains additional material and exercises. Keywords: Environmental Monitoring, Experimental Design, R?umliche Daten, R?umliche Statistik, Spatial Data, Spatial Statistics, Umweltmonitoring, Umweltmonotoring, Versuchsplanung -- TWikiAdminUser - 2010-06-04 |

Book Title: Collecting Spatial Data (2nd Ed)
-- TWikiAdminUser - 2010-06-04 |

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