
- 168 pages
- English
- ePUB (mobile friendly)
- Available on iOS & Android
About this book
Theory of Spatial Statistics: A Concise Introduction presents the most important models used in spatial statistics, including random fields and point processes, from a rigorous mathematical point of view and shows how to carry out statistical inference. It contains full proofs, real-life examples and theoretical exercises. Solutions to the latter are available in an appendix.Assuming maturity in probability and statistics, these concise lecture notes are self-contained and cover enough material for a semester course. They may also serve as a reference book for researchers. Features * Presents the mathematical foundations of spatial statistics.
* Contains worked examples from mining, disease mapping, forestry, soil and environmental science, and criminology.
* Gives pointers to the literature to facilitate further study.
* Provides example code in R to encourage the student to experiment.
* Offers exercises and their solutions to test and deepen understanding.The book is suitable for postgraduate and advanced undergraduate students in mathematics and statistics.
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Information
Table of contents
- Cover
- Half Title
- Title Page
- Copyright Page
- Dedication
- Contents
- Preface
- Author
- Chapter 1: Introduction
- Chapter 2: Random field modelling and interpolation
- Chapter 3: Models and inference for areal unit data
- Chapter 4: Spatial point processes
- Appendix: Solutions to theoretical exercises
- Index