Spatial Statistics for Data Science with R by Paula Moraga
Book Contents :-
SPATIAL DATA
1. Types of Spatial Data
2. Spatial Data in R
3. The sf Package for Spatial Vector Data
4. The terra Package for Raster and Vector Data
5. Making Maps with R
6. R Packages to Download Open Spatial Data
AREAL DATA
7. Spatial Neighborhood Matrices
8. Spatial Autocorrelation
9. Bayesian Spatial Models
10. Disease Risk Modeling
11. Areal Data Issues
GEOSTATISTICAL DATA
12. Geostatistical Data
13. Spatial Interpolation Methods
14. Kriging
15. Model-Based Geostatistics
16. Methods Assessment
SPATIAL POINT PATTERNS
17. Spatial Point Patterns
18. The spatstat Package
19. Spatial Point Processes and Simulation
20. Complete Spatial Randomness
21. Intensity Estimation
22. The K-Function
23. Point Process Modeling
About this book :-
"Spatial Statistics for Data Science: Theory and Practice with R" by Paula Moraga is a practical guide to understanding how location-based data can be analyzed using modern statistical methods. The book introduces key ideas in spatial analysis, helping readers explore how geography influences data patterns. It is written in a clear and accessible style, making it suitable for students and beginners in data science.
The book focuses heavily on hands-on learning with R programming language, providing real-world examples and datasets. It covers essential topics such as spatial data visualization, spatial autocorrelation, geostatistics, and point pattern analysis. Advanced methods like interpolation, kriging, and Bayesian spatial models are also explained, allowing readers to build deeper analytical skills.
Overall, this book is ideal for learners who want to apply "spatial statistics", "data science", "R programming", "geostatistics", and "data visualization" in real-world scenarios. It bridges theory and practice, helping readers analyze geographic data in fields like public health, environment, and urban planning with confidence.
Book Detail :-
Title:
Spatial Statistics for Data Science with R by Paula Moraga
Publisher:
Chapman and Hall/CRC
Year:
2023
Pages:
285
Type:
PDF
Language:
English
ISBN-10 #:
1032633514
ISBN-13 #:
978-1032633510
License:
CC BY-NC-ND 4.0
Amazon:
Amazon
About Author :-
The author
Paula Moraga
is a Spanish statistician and academic with a strong background in "spatial statistics" and applied data science. She earned her PhD in Mathematics from the University of Valencia and a Master’s in Biostatistics from Harvard University. Over her career, she has held positions at institutions like Lancaster University and the London School of Hygiene & Tropical Medicine, currently serving as a professor at KAUST. Her expertise spans "geospatial data analysis, epidemiology, R programming, disease surveillance, and statistical modeling". Moraga focuses on analyzing geographic patterns of health data, creating practical tools for researchers and policymakers. Her work bridges data science and public health, enabling informed decision-making with spatial data.
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