Spatial Linear Models for Environmental Data

Spatial Linear Models for Environmental Data
Author :
Publisher : CRC Press
Total Pages : 899
Release :
ISBN-10 : 9780429593802
ISBN-13 : 0429593805
Rating : 4/5 (805 Downloads)

Book Synopsis Spatial Linear Models for Environmental Data by : Dale L. Zimmerman

Download or read book Spatial Linear Models for Environmental Data written by Dale L. Zimmerman and published by CRC Press. This book was released on 2024-04-17 with total page 899 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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. Spatial Linear Models for Environmental Data, aimed at students and professionals with a master’s level training in statistics, presents a unique, applied, and thorough treatment of spatial linear models within a statistics framework. Two subfields, one called geostatistics and the other called areal or lattice models, are extensively covered. Zimmerman and Ver Hoef present topics clearly, using many examples and simulation studies to illustrate ideas. By mimicking their examples and R code, readers will be able to fit spatial linear models to their data and draw proper scientific conclusions. Topics covered include: Exploratory methods for spatial data including outlier detection, (semi)variograms, Moran’s I, and Geary’s c. Ordinary and generalized least squares regression methods and their application to spatial data. Suitable parametric models for the mean and covariance structure of geostatistical and areal data. Model-fitting, including inference methods for explanatory variables and likelihood-based methods for covariance parameters. Practical use of spatial linear models including prediction (kriging), spatial sampling, and spatial design of experiments for solving real world problems. All concepts are introduced in a natural order and illustrated throughout the book using four datasets. All analyses, tables, and figures are completely reproducible using open-source R code provided at a GitHub site. Exercises are given at the end of each chapter, with full solutions provided on an instructor’s FTP site supplied by the publisher.


Spatial Linear Models for Environmental Data Related Books

Spatial Linear Models for Environmental Data
Language: en
Pages: 899
Authors: Dale L. Zimmerman
Categories: Mathematics
Type: BOOK - Published: 2024-04-17 - Publisher: CRC Press

DOWNLOAD EBOOK

Many applied researchers equate spatial statistics with prediction or mapping, but this book naturally extends linear models, which includes regression and ANOV
Spatial Modeling in GIS and R for Earth and Environmental Sciences
Language: en
Pages: 800
Authors: Hamid Reza Pourghasemi
Categories: Science
Type: BOOK - Published: 2019-01-18 - Publisher: Elsevier

DOWNLOAD EBOOK

Spatial Modeling in GIS and R for Earth and Environmental Sciences offers an integrated approach to spatial modelling using both GIS and R. Given the importance
Spatial Linear Models for Environmental Data
Language: en
Pages: 400
Authors: Dale L. Zimmerman
Categories: Mathematics
Type: BOOK - Published: 2024-04-17 - Publisher: CRC Press

DOWNLOAD EBOOK

Many applied researchers equate spatial statistics with prediction or mapping, but this book naturally extends linear models, which includes regression and ANOV
Geographically Weighted Regression
Language: en
Pages: 282
Authors: A. Stewart Fotheringham
Categories: Science
Type: BOOK - Published: 2003-02-21 - Publisher: John Wiley & Sons

DOWNLOAD EBOOK

Geographical Weighted Regression (GWR) is a new local modelling technique for analysing spatial analysis. This technique allows local as opposed to global model
Spatial Regression Analysis Using Eigenvector Spatial Filtering
Language: en
Pages: 288
Authors: Daniel Griffith
Categories: Business & Economics
Type: BOOK - Published: 2019-09-14 - Publisher: Academic Press

DOWNLOAD EBOOK

Spatial Regression Analysis Using Eigenvector Spatial Filtering provides theoretical foundations and guides practical implementation of the Moran eigenvector sp