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Spatial statistics for data science ...

Moraga, Paula,

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

Record Type:	Language materials, printed : Monograph/item
Title/Author:	Spatial statistics for data science :/ Paula Moraga.
Reminder of title:	theory and practice with R /
Author:	Moraga, Paula,
Published:	Boca Raton :CRC Press, Taylor & Francis Group, : 2024.,
Description:	xvii, 279 p. :ill. (some col.), maps (chiefly col.) ;24 cm.
Subject:	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 :CRC Press, Taylor & Francis Group,2024. - xvii, 279 p. :ill. (some col.), maps (chiefly col.) ;24 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: 9781032633510GBP81.99

LCCN: 2023035998Subjects--Topical Terms:

520421
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 /
LDR:02342cam a2200301 a 4500 001 2379276
003 OCoLC
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008 250320s2024 fluab b 001 0 eng
010 $a 2023035998
019 $a 1452509553
020 $a 9781032633510 $q (hbk.) : $c GBP81.99
020 $a 1032633514 $q (hbk.)
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035 $a (OCoLC)1405845749 $z (OCoLC)1452509553
040 $a DLC $b eng $c DLC $d OCLCO $d CLE $d OCLCO $d AU@ $d IG#
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050 0 0 $a QA278.2 $b .M684 2024
082 0 0 $a 001.4/22 $2 23
100 1 $a Moraga, Paula, $e author. $3 3743800
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 : $b CRC Press, Taylor & Francis Group, $c 2024.
300 $a xvii, 279 p. : $b ill. (some col.), maps (chiefly col.) ; $c 24 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 520421
650 # 0 $a R (Computer program language) $3 784593
776 0 8 $i Online version: $a Moraga, Paula. $t Spatial statistics for data science $b First edition $d Boca Raton, FL : CRC Press is an imprint of Taylor & Francis Group, LLC, 2024 $z 9781032641522 $w (DLC) 2023035999
830 0 $a Chapman & Hall/CRC data science series. $3 3536948