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A user's guide to network analysis in R

Luke, Douglas A.

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A user's guide to network analysis in R

Record Type:	Electronic resources : Monograph/item
Title/Author:	A user's guide to network analysis in R/ by Douglas A. Luke.
Author:	Luke, Douglas A.
Published:	Cham :Springer International Publishing : : 2015.,
Description:	xii, 238 p. :ill., digital ;24 cm.
[NT 15003449]:	Introducing Network Analysis in R -- The Network Analysis "5 Number Summary" -- Network Data Management in R -- Basic Network Plotting and Layout -- Effective Network Graphic Design -- Advanced Network Graphics -- Actor Prominence -- Subgroups -- Affiliation Networks -- Random Network Models -- Statistical Network Models -- Dynamic Network Models -- Simulations.
Contained By:	Springer eBooks
Subject:	Social sciences - Network analysis -
Online resource:	http://dx.doi.org/10.1007/978-3-319-23883-8
ISBN:	9783319238838$q(electronic bk.)

A user's guide to network analysis in R
Luke, Douglas A.

A user's guide to network analysis in R[electronic resource] /by Douglas A. Luke. - Cham :Springer International Publishing :2015. - xii, 238 p. :ill., digital ;24 cm. - Use R!,2197-5736. - Use R!.

Introducing Network Analysis in R -- The Network Analysis "5 Number Summary" -- Network Data Management in R -- Basic Network Plotting and Layout -- Effective Network Graphic Design -- Advanced Network Graphics -- Actor Prominence -- Subgroups -- Affiliation Networks -- Random Network Models -- Statistical Network Models -- Dynamic Network Models -- Simulations.

Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.

ISBN: 9783319238838$q(electronic bk.)

Standard No.: 10.1007/978-3-319-23883-8doiSubjects--Topical Terms:

2165638
Social sciences
--Network analysis

LC Class. No.: HM741

Dewey Class. No.: 302.30285

A user's guide to network analysis in R
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245 1 2 $a A user's guide to network analysis in R $h [electronic resource] / $c by Douglas A. Luke.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2015.
300 $a xii, 238 p. : $b ill., digital ; $c 24 cm.
490 1 $a Use R!, $x 2197-5736
505 0 $a Introducing Network Analysis in R -- The Network Analysis "5 Number Summary" -- Network Data Management in R -- Basic Network Plotting and Layout -- Effective Network Graphic Design -- Advanced Network Graphics -- Actor Prominence -- Subgroups -- Affiliation Networks -- Random Network Models -- Statistical Network Models -- Dynamic Network Models -- Simulations.
520 $a Presenting a comprehensive resource for the mastery of network analysis in R, the goal of Network Analysis with R is to introduce modern network analysis techniques in R to social, physical, and health scientists. The mathematical foundations of network analysis are emphasized in an accessible way and readers are guided through the basic steps of network studies: network conceptualization, data collection and management, network description, visualization, and building and testing statistical models of networks. As with all of the books in the Use R! series, each chapter contains extensive R code and detailed visualizations of datasets. Appendices will describe the R network packages and the datasets used in the book. An R package developed specifically for the book, available to readers on GitHub, contains relevant code and real-world network datasets as well.
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950 $a Mathematics and Statistics (Springer-11649)