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Spatial statistics for data science :theory and practice with R /

紀錄類型:	書目-語言資料,印刷品 : Monograph/item
正題名/作者:	Spatial statistics for data science :Paula Moraga.
其他題名:	theory and practice with R /
作者:	Moraga, Paula,
出版者:	Boca Raton, FL :CRC Press, Taylor & Francis Group,2024.
面頁冊數:	xvii, 279 p. :ill. (some col.), maps (some col.) ;25 cm.
標題:	Spatial analysis (Statistics)
ISBN:	9781032633510 :

Spatial statistics for data science :theory and practice with R /
Moraga, Paula,

Spatial statistics for data science :theory and practice with R /Paula Moraga. - 1st ed. - Boca Raton, FL :CRC Press, Taylor & Francis Group,2024. - xvii, 279 p. :ill. (some col.), maps (some col.) ;25 cm. - Chapman & Hall/CRC data science series. - Chapman & Hall/CRC data science series..

Includes bibliographical references (p. 267-276) and index.

"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"--

ISBN: 9781032633510 :NT$3218

LCCN: 2023035998Subjects--Topical Terms:

185012
Spatial analysis (Statistics)

LC Class. No.: QA278.2 / .M684 2024

Dewey Class. No.: 001.4/22

Spatial statistics for data science :theory and practice with R /
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245 1 0 $a Spatial statistics for data science : $b theory and practice with R / $c Paula Moraga.
250 $a 1st ed.
260 $a Boca Raton, FL : $b CRC Press, Taylor & Francis Group, $c 2024.
300 $a xvii, 279 p. : $b ill. (some col.), maps (some col.) ; $c 25 cm.
490 1 $a Chapman & Hall/CRC data science series
504 $a Includes bibliographical references (p. 267-276) and index.
520 $a "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"-- $c Provided by publisher.
650 0 $a Spatial analysis (Statistics) $3 185012
650 0 $a R (Computer program language) $3 210846
830 0 $a Chapman & Hall/CRC data science series. $3 913818