Opening book details…
Can I read Spatial Statistics for Data Science: Theory and Practice with R on EtoBox?
Spatial Statistics for Data Science: Theory and Practice with R by Paula Moraga is a book available to read on EtoBox.
What is Spatial Statistics for Data Science: Theory and Practice with R about?
Spatial data is crucial to improve decision-making in a wide range of fields including environment, health, ecology, urban planning, economy, and society. Spatial Statistics for Data Science: Theory and Practice with R describes statistical methods, modeling approaches, and visualization techniques to analyze spatial data using R. The book provides a comprehensive overview of the varying types of spatial data, and detailed explanations of the theoretical concepts of spatial statistics, alongside fully reproducible examples which demonstrate how to simulate, describe, and analyze spatial data in various applications. Combining theory and practice, the book includes real-world data science examples such as disease risk mapping, air pollution prediction, species distribution modeling, crime mapping, and real state analyses. The book utilizes publicly available data and offers clear explanations of the R code for importing, manipulating, analyzing, and visualizing data, as well as the interpretation of the results. This ensures contents are easily accessible and fully reproducible for students, researchers, and practitioners. Key Features: • Describes R packages for retrieval, manipula
- Author
- Paula Moraga
- Publisher
- CRC Press
- Published
- 2024
- Language
- EN
More by Paula Moraga
Browse all works by Paula Moraga
Similar books
- Practical Data Science with R — Nina Zumel & John Mount Nina Zumel and John Mount (2014)
- Statistics for Spatial Data — Noel A. C. Cressie (1993)
- Spatial Predictive Modelling with R — Jin Li, Taylor & Francis Group (2022)
- Easy Statistics for Food Science with R — Abbas F. M. Alkarkhi, Wasin A. Alqaraghuli, Abbas F. Mubarek Al-Karkhi (2019)
- Statistics and Data Visualization in Climate Science with R and Python — Samual S. P. Shen; Gerald R. North (2023)
- Spatial Analysis Using Big Data: Methods and Urban Applications (Spatial Econometrics and Spatial Statistics) — Yoshiki Yamagata (2019)