Spatial Statistics for Data Science: Theory and Practice with R

Moraga, Paula

Spatial Statistics for Data Science: Theory and Practice with R
  • 出版商: CRC
  • 出版日期: 2023-12-08
  • 售價: $3,510
  • 貴賓價: 9.5 折 $3,335
  • 語言: 英文
  • 頁數: 280
  • 裝訂: Hardcover - also called cloth, retail trade, or trade
  • ISBN: 1032633514
  • ISBN-13: 9781032633510
  • 相關分類: 機率統計學 Probability-and-statistics、Data Science

    • 下單後立即進貨 (約2~4週)

相關主題

商品描述

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, manipulation, and visualization of spatial data
  • Offers a comprehensive overview of spatial statistical methods including spatial autocorrelation, clustering, spatial interpolation, model-based geostatistics, and spatial point processes
  • Provides detailed explanations on how to fit and interpret Bayesian spatial models using the integrated nested Laplace approximation (INLA) and stochastic partial differential equation (SPDE) approaches

商品描述(中文翻譯)

空間數據對於改善決策在各個領域中至關重要，包括環境、健康、生態、城市規劃、經濟和社會等。《空間統計學與資料科學：使用R的理論與實踐》描述了使用R進行空間數據分析的統計方法、建模方法和可視化技術。該書全面介紹了不同類型的空間數據，並詳細解釋了空間統計的理論概念，並提供了完全可重現的示例，演示如何在各種應用中模擬、描述和分析空間數據。結合理論和實踐，該書包括實際的數據科學示例，如疾病風險地圖、空氣污染預測、物種分布建模、犯罪地圖和房地產分析。該書利用公開可用的數據，清晰解釋了R代碼的導入、操作、分析和可視化數據，以及結果的解釋。這確保內容對學生、研究人員和從業人員易於訪問並完全可重現。

主要特點：
- 描述了用於檢索、操作和可視化空間數據的R包
- 提供了空間統計方法的全面概述，包括空間自相關、聚類、空間插值、基於模型的地理統計和空間點過程
- 詳細解釋了如何使用集成嵌套拉普拉斯近似（INLA）和隨機偏微分方程（SPDE）方法擬合和解釋貝葉斯空間模型。

作者簡介

Paula Moraga is Professor of Statistics at King Abdullah University of Science and Technology (KAUST). She received her Master's in Biostatistics from Harvard University and her Ph.D. in Mathematics from the University of Valencia. Dr. Moraga develops innovative statistical methods and open-source software for spatial data analysis and health surveillance, including R packages for spatio-temporal modeling, detection of clusters, and travel-related spread of disease. Her work has directly informed strategic policy in reducing the burden of diseases such as malaria and cancer in several countries. Dr. Moraga has published extensively in leading journals, and serves as an Associate Editor of the Journal of the Royal Statistical Society Series A. She is the author of the book Geospatial Health Data: Modeling and Visualization with R-INLA and Shiny (Chapman & Hall/CRC). Dr. Moraga received the prestigious Letten Prize for her pioneering research in disease surveillance, and her significant contributions in the development of sustainable solutions to health and environmental challenges globally.

作者簡介(中文翻譯)

Paula Moraga 是沙特阿拉伯國王阿卜杜拉科技大學（KAUST）的統計學教授。她在哈佛大學獲得生物統計學碩士學位，並在瓦倫西亞大學獲得數學博士學位。Moraga博士開發了創新的統計方法和開源軟件，用於空間數據分析和健康監測，包括用於時空建模、集群檢測和疾病傳播的旅行相關R軟件包。她的工作直接影響了多個國家減輕疟疾和癌症等疾病負擔的戰略政策。Moraga博士在領先期刊上發表了大量論文，並擔任《皇家統計學會A系列期刊》的副編輯。她是書籍《地理健康數據：使用R-INLA和Shiny進行建模和可視化》（Chapman＆Hall / CRC）的作者。Moraga博士因在疾病監測方面的開創性研究和在全球健康和環境挑戰的可持續解決方案開發中的重要貢獻而獲得了著名的Letten獎。

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