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Statistical analysis of network data : methods and models / Eric D. Kolaczyk.

By: Kolaczyk, Eric DMaterial type: TextTextLanguage: English Series: Springer series in statisticsPublication details: New York ; [London] : Springer, c2009. Description: xii, 386 p. : ill. ; 24 cmISBN: 9780387881454 (acidfree paper); 038788145X (acidfree paper)Subject(s): System analysis -- Statistical methods | Analyse de systèmes -- Méthodes statistiquesDDC classification: 519.5 LOC classification: QA402 | .K648 2009Online resources: WorldCat details | Ebook Fulltext
Contents:
TOC and Overview.- Preliminaries.- Mapping Networks.- Descriptive Analysis of Network Graph Characteristics.- Sampling and Estimation in Network Graphs.- Models for Network Graphs.- Network Topology Inference.- Modeling and Prediction for Processes on Network Graphs.- Analysis of Network Flow Data.- Graphical Models.
Summary: This text provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation entails a conscious balance of concepts versus mathematics.
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Holdings
Item type Current library Collection Call number Copy number Status Date due Barcode Item holds
E-Book E-Book Dr. S. R. Lasker Library, EWU
E-book 		Non-fiction 519.5 KOS 2009 (Browse shelf(Opens below)) Not for loan
Text Text Dr. S. R. Lasker Library, EWU
Reserve Section 		Non-fiction 519.5 KOS 2009 (Browse shelf(Opens below)) C-1 Not For Loan 26680
Total holds: 0

Includes bibliographical references (p. 347-371) and index.

TOC and Overview.- Preliminaries.- Mapping Networks.- Descriptive Analysis of Network Graph Characteristics.- Sampling and Estimation in Network Graphs.- Models for Network Graphs.- Network Topology Inference.- Modeling and Prediction for Processes on Network Graphs.- Analysis of Network Flow Data.- Graphical Models.


This text provides an up-to-date treatment of the foundations common to the statistical analysis of network data across the disciplines. The material is organized according to a statistical taxonomy, although the presentation entails a conscious balance of concepts versus mathematics.

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Tahur Ahmed

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