Dale L. Zimmerman, Jay M. Ver Hoef

Spatial Linear Models for Environmental Data (eBook, PDF)

• Format: PDF

Produktbeschreibung

Many applied researchers equate spatial statistics with prediction or mapping, but this book naturally extends linear models, which includes regression and ANOVA as pillars of applied statistics, to achieve a more comprehensive treatment of the analysis of spatially autocorrelated data.

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Produktdetails

• Verlag: Taylor & Francis
• Seitenzahl: 416
• Erscheinungstermin: 17. April 2024
• Englisch
• ISBN-13: 9780429595097
• Artikelnr.: 70096833

Autorenporträt

Dale L. Zimmerman is Professor of Statistics at the University of Iowa, and Jay M. Ver Hoef is Senior Scientist and Statistician, Alaska Fisheries Science Center, NOAA Fisheries. Both are Fellows of the American Statistical Association and winners of that association's Section for Statistics and the Environment Distinguished Achievement Award.

Inhaltsangabe

Preface 1. Introduction 2. An Introduction to Covariance Structures for
Spatial Linear Models 3. Exploratory Spatial Data Analysis 4. Provisional
Estimation of the Mean Structure by Ordinary Least Squares 5. Generalized
Least Squares Estimation of the Mean Structure 6. Parametric Covariance
Structures for Geostatistical Models 7. Parametric Covariance Structures
for Spatial-Weights Linear Models 8. Likelihood-Based Inference 9. Spatial
Prediction 10. Spatial Sampling Design 11. Analysis and Design of Spatial
Experiments 12. Extensions Appendix A: Some Matrix Results