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170815s2014 nyu eng |
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|a 1493909827
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|a 9781493909827
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|a 9781493909834
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|a UniSZA
|e rda
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|a QA402
|b .K65 2014
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|a QA402
|b .K65 2014
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| 100 |
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|a Kolaczyk, Eric D. ,
|e author
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| 245 |
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|a Statistical analysis of network data with R
|c Eric D. Kolaczyk, Gaabor Csaardi
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| 264 |
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|a New York :
|b Springer
|c c2014
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| 300 |
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|a xiii, 207 pages :
|b illustration (some colour) ;
|c 24 cm.
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| 336 |
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|a text
|2 rdacontent
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| 337 |
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|a unmediated
|2 rdamedia
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| 338 |
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|a volume
|2 rdacarrier
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| 490 |
1 |
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|a Use R!
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| 504 |
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|a Includes bibliographical references (pages 197- 204) and index
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|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. Modelling and prediction for processes on network graphs -- 9. Analysis of network flow data -- 10. Dynamic networks
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| 520 |
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|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 bac
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| 650 |
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|a R (Computer program language)
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| 650 |
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|a System analysis
|x Statistical methods
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| 650 |
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|a Systems Analysis
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| 700 |
1 |
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|a Csaardi, Gaabor ,
|e author
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| 999 |
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|a 1000169460
|b Book
|c OPEN SHELF (30 DAYS)
|e Tembila Campus
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