Statistical analysis of network data with R

Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back cent...

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Permalink: http://skupni.nsk.hr/Record/fer.KOHA-OAI-FER:44377/Details
Glavni autor: Kolaczyk, Eric D. (-)
Ostali autori: Csárdi, Gábor (-)
Vrsta građe: Knjiga
Jezik: eng
Impresum: New York: Springer, 2014.
Nakladnička cjelina: Use R!
Predmet:
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010 |a  2014936989 
020 |a 9781493909827 (pbk. : alk. paper) 
020 |a 1493909827 (pbk. : alk. paper) 
020 |z 9781493909834 (eBook) 
040 |a YDXCP  |b eng  |c YDXCP  |e rda  |d BTCTA  |d OCLCO  |d MUU  |d RCE  |d OCLCF  |d HR-ZaFER 
042 |a lccopycat 
050 0 0 |a QA402  |b .K6483 2014 
082 0 4 |a 003.015195  |2 23 
100 1 |a Kolaczyk, Eric D. 
245 1 0 |a Statistical analysis of network data with R /  |c Eric D. Kolaczyk, Gábor Csárdi. 
260 |a New York:  |b Springer,  |c 2014. 
300 |a xiii, 207 str. :  |b ilustr. u bojama;  |c 24 cm. 
490 1 |a Use R! 
504 |a Includes bibliographical references (197-204) and index 
505 0 |a 1. Introduction -- 2. Manipulating network data -- 3. Visualizing network data -- 4. Descriptive analysis of network graph characteristics -- 5. Mathematical models for network graphs -- 6. Statistical models for network graphs -- 7. Network topology inference -- 8. Modeling and prediction for processes on network graphs -- 9. Analysis of network flow data -- 10. Dynamic networks. 
520 3 |a Networks have permeated everyday life through everyday realities like the Internet, social networks, and viral marketing. As such, network analysis is an important growth area in the quantitative sciences, with roots in social network analysis going back to the 1930s and graph theory going back centuries. Measurement and analysis are integral components of network research. As a result, statistical methods play a critical role in network analysis. This book is the first of its kind in network research. It can be used as a stand-alone resource in which multiple R packages are used to illustrate how to conduct a wide range of network analyses, from basic manipulation and visualization, to summary and characterization, to modeling of network data. The central package is igraph, which provides extensive capabilities for studying network graphs in R. This text builds on Eric D. Kolaczyk's book Statistical Analysis of Network Data (Springer, 2009).-- 
650 0 |a System analysis  |x Statistical methods. 
650 0 |a R (Computer program language) 
650 1 2 |a Data Interpretation, Statistical. 
650 7 |a R (Computer program language)  |2 fast 
650 7 |a System analysis  |x Statistical methods.  |2 fast 
700 1 |a Csárdi, Gábor. 
830 0 |a Use R! 
906 |a 7  |b cbc  |c copycat  |d 2  |e epcn  |f 20  |g y-gencatlg 
942 |2 udc  |c K 
955 |b rl09 2015-02-10 z-processor  |i rl09 2015-02-12 ; to BCCD 
955 |a pc17 2014-03-31 
999 |c 44377  |d 44377