Difference: Books20100611112619 (1 vs. 4)

Revision 42010-08-13 - TheresiaFreska

 
META TOPICPARENT name="AI_GEOSTATSBooks"
Book Title: Collecting Spatial Data (2nd Ed)

ISBN: 3790813338

Book Author(s): Werner G. Müller

Book Publisher: Springer Verlag

Date of Publication: 1 October 2000

Cost: 100 US$

Pages: 186

Url: http://www.springer.com/

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. 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.

Deleted:
<
<
-- TWikiAdminUser - 2010-06-04

Revision 32010-07-23 - TWikiAdminUser

 
META TOPICPARENT name="AI_GEOSTATSBooks"
Book Title: Collecting Spatial Data (2nd Ed)

ISBN: 3790813338

Changed:
<
<
Book Author(s): Werner G. M?ller
>
>
Book Author(s): Werner G. Müller
  Book Publisher: Springer Verlag
Changed:
<
<
Date of Publication:
>
>
Date of Publication: 1 October 2000
  Cost: 100 US$

Pages: 186

Url: http://www.springer.com/

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. 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

Changed:
<
<
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.
  -- TWikiAdminUser - 2010-06-04

Revision 22010-07-23 - TWikiAdminUser

Changed:
<
<
META TOPICPARENT name="GeostatisticsBooks"
>
>
META TOPICPARENT name="AI_GEOSTATSBooks"
 Book Title: Collecting Spatial Data (2nd Ed)

ISBN: 3790813338

Book Author(s): Werner G. M?ller

Book Publisher: Springer Verlag

Date of Publication:

Cost: 100 US$

Pages: 186

Url: http://www.springer.com/

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. 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.

-- TWikiAdminUser - 2010-06-04

Revision 12010-06-11 - TWikiAdminUser

 
META TOPICPARENT name="GeostatisticsBooks"
Book Title: Collecting Spatial Data (2nd Ed)

ISBN: 3790813338

Book Author(s): Werner G. M?ller

Book Publisher: Springer Verlag

Date of Publication:

Cost: 100 US$

Pages: 186

Url: http://www.springer.com/

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. 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.

-- TWikiAdminUser - 2010-06-04

 
This site is powered by the TWiki collaboration platformCopyright © by the contributing authors. All material on this collaboration platform is the property of the contributing authors.
Ideas, requests, problems regarding TWiki? Send feedback