000			04177nam a22005415i 4500
001			978-0-387-88146-1
003			DE-He213
005			20251006084428.0
007			cr nn 008mamaa
008			100301s2009 xxu| s |||| 0|eng d
020			_a9780387881461
020			_a99780387881461
024	7		_a10.1007/978-0-387-88146-1 _2doi
100	1		_aKolaczyk, Eric D. _eauthor.
245	1	0	_aStatistical Analysis of Network Data _h[electronic resource] : _bMethods and Models / _cby Eric D. Kolaczyk.
264		1	_aNew York, NY : _bSpringer New York, _c2009.
300			_bonline resource.
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
347			_atext file _bPDF _2rda
490	1		_aSpringer Series in Statistics, _x0172-7397
505	0		_aand 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.
520			_aIn the past decade, the study of networks has increased dramatically. Researchers from across the sciences-including biology and bioinformatics, computer science, economics, engineering, mathematics, physics, sociology, and statistics-are more and more involved with the collection and statistical analysis of network-indexed data. As a result, statistical methods and models are being developed in this area at a furious pace, with contributions coming from a wide spectrum of disciplines. This book 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. In addition, the examples-including extended cases studies-are drawn widely from the literature. This book should be of substantial interest both to statisticians and to anyone else working in the area of 'network science.' The coverage of topics in this book is broad, but unfolds in a systematic manner, moving from descriptive (or exploratory) methods, to sampling, to modeling and inference. Specific topics include network mapping, characterization of network structure, network sampling, and the modeling, inference, and prediction of networks, network processes, and network flows. This book is the first such resource to present material on all of these core topics in one place. Eric Kolaczyk is a professor of statistics, and Director of the Program in Statistics, in the Department of Mathematics and Statistics at Boston University, where he also is an affiliated faculty member in the Center for Biodynamics, the Program in Bioinformatics, and the Division of Systems Engineering. His publications on network-based topics include work ranging from the detection of anomalous traffic patterns in computer networks to the prediction of biological function in networks of interacting proteins to the characterization of influence of groups of actors in social networks.
650		0	_aSTATISTICS.
650		0	_aDATA MINING.
650		0	_aBIOINFORMATICS.
650		0	_aPHYSICS.
650		0	_aMATHEMATICAL STATISTICS.
650		0	_aENGINEERING.
650		0	_aTELECOMMUNICATION.
650		0	_aSOCIAL SCIENCES _xMETHODOLOGY.
650	1	4	_aSTATISTICS.
650	2	4	_aCOMMUNICATIONS ENGINEERING, NETWORKS.
650	2	4	_aMETHODOLOGY OF THE SOCIAL SCIENCES.
650	2	4	_aBIOINFORMATICS.
650	2	4	_aDATA MINING AND KNOWLEDGE DISCOVERY.
650	2	4	_aCOMPLEXITY.
650	2	4	_aSTATISTICAL THEORY AND METHODS.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9780387881454
830		0	_aSpringer Series in Statistics, _x0172-7397
856	4	0	_uhttp://dx.doi.org/10.1007/978-0-387-88146-1 _zVer el texto completo en las instalaciones del CICY
912			_aZDB-2-SMA
942			_2ddc _cER
999			_c59360 _d59360