Spatial Linear Models for Environmental Data

ISBN-13: 9780367183349 / Angielski

Dale L. Zimmerman; Jay M. Ver Hoef

Opis

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.

Spis treści

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

O autorze

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.