Spatial Data Analysis With R
eBook - ePub

Spatial Data Analysis With R

  1. English
  2. ePUB (mobile friendly)
  3. Available on iOS & Android
eBook - ePub

Spatial Data Analysis With R

About this book

This is an introduction for social science students to the growing field of spatial data analysis using the R platform. The text assumes no prior knowledge of either, beyond the contents of an introductory statistics course. It uses the open-source software R, and relevant spatial data analysis packages, to provide practical guidance of how to conduct spatial data analysis with readers? own data sets. The book first briefly introduces students to R, covers some basic concepts in statistical data analysis, and then focuses on discussing the central ideas of spatial data analysis. All the discussions are supported with R scripts so that students can work on their own and produce results that the book helps interpret. Each chapter ends with review questions to test understanding. The book is suited for upper-level undergraduate social science students and graduate students, and other social scientists who are interested in analyzing their spatial data with R.

A companion website for the book can be found on the Resources tab above. It includes R code and data for students to replicate the examples in the book. The password-protected instructor side of the site includes exercises and answers which can be set for homework.




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Table of contents

  1. Cover
  2. Half Title
  3. Endorsements
  4. Title Page
  5. Copyright Page
  6. Brief Contents
  7. Detailed Contents
  8. Preface
  9. Acknowledgments
  10. About the Author
  11. 1 The Journey Starts With R
  12. 2 Very Basic Concepts of Statistical Data Analysis
  13. 3 Spatial Data is Special: Working With the Complexity of Spatial Data
  14. 4 The Concept of Neighbor: Spatial Linkage Matrix and Spatial Weight
  15. 5 Global Spatial Autocorrelation
  16. 6 Local Spatial Autocorrelation
  17. 7 Spatial Autoregressive Models
  18. 8 Eigenfunction-Based Spatial Filtering Regression
  19. 9 Introduction to Local Models: Geographically Weighted Regression and Eigenfunction-Based Spatial Filtering Approach
  20. 10 Brief Introduction to Spatial Panel Regression and SVC Panel Regression
  21. 11 Conclusion
  22. Appendix: Answers to Review Questions
  23. References
  24. Index

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Yes, you can access Spatial Data Analysis With R by Danlin Yu in PDF and/or ePUB format, as well as other popular books in Social Sciences & Social Science Research & Methodology. We have over one million books available in our catalogue for you to explore.