000 04329nam a22005415i 4500
001 978-3-030-26814-5
003 DE-He213
005 20200812131809.0
007 cr nn 008mamaa
008 191119s2019 gw | s |||| 0|eng d
020 _a9783030268145
_9978-3-030-26814-5
024 7 _a10.1007/978-3-030-26814-5
_2doi
040 _cCUS
050 4 _aQA276-280
072 7 _aPBT
_2bicssc
072 7 _aMAT029000
_2bisacsh
072 7 _aPBT
_2thema
082 0 4 _a519.5
_223
245 1 0 _aNetwork Science
_h[electronic resource] :
_bAn Aerial View /
_cedited by Francesca Biagini, Göran Kauermann, Thilo Meyer-Brandis.
250 _a1st ed. 2019.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2019.
300 _aIX, 119 p. 37 illus., 16 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
505 0 _aPreface -- Introduction (Francesca Biagini, Göran Kauermann, Thilo Meyer-Brandis) -- Network Visualization (Ulrik Brandes and Michael Sedlmair) -- A Statistician’s View of Network Modeling (David R. Hunter) -- The Rank-one and the Preferential Attachment Paradigm (Steffen Dereich) -- Systemic Risk in Networks (Nils Detering, Thilo Meyer-Brandis, Konstantinos Panagiotou, Daniel Ritter) -- Bayesian Networks for Max-linear Models (Claudia Klüppelberg, Steffen Lauritzen) -- Introduction to Network Inference in Genomics (Ernst C. Wit).
520 _aThis book provides an overview of network science from the perspective of diverse academic fields, offering insights into the various research areas within network science. The authoritative contributions on statistical network analysis, mathematical network science, genetic networks, Bayesian networks, network visualisation, and systemic risk in networks explore the main questions in the respective fields: What has been achieved to date? What are the research challenges and obstacles? What are the possible interconnections with other fields? And how can cross-fertilization between these fields be promoted? Network Science comprises numerous scientific disciplines, including computer science, economics, mathematics, statistics, social sciences, bioinformatics, and medicine, among many others. These diverse research areas require and use different data-analytic and numerical methods as well as different theoretical approaches. Nevertheless, they all examine and describe interdependencies, associations, and relationships of entities in different kinds of networks. The book is intended for researchers as well as interested readers working in network science who want to learn more about the field – beyond their own research or work niche. Presenting network science from different perspectives without going into too much technical detail, it allows readers to gain an overview without having to be a specialist in any or all of these disciplines.
650 0 _aStatistics .
650 0 _aProbabilities.
650 0 _aMathematical statistics.
650 0 _aSystem theory.
650 0 _aApplication software.
650 1 4 _aStatistical Theory and Methods.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S11001
650 2 4 _aProbability Theory and Stochastic Processes.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M27004
650 2 4 _aProbability and Statistics in Computer Science.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I17036
650 2 4 _aComplex Systems.
_0https://scigraph.springernature.com/ontologies/product-market-codes/M13090
650 2 4 _aComputer Appl. in Social and Behavioral Sciences.
_0https://scigraph.springernature.com/ontologies/product-market-codes/I23028
650 2 4 _aStatistics for Life Sciences, Medicine, Health Sciences.
_0https://scigraph.springernature.com/ontologies/product-market-codes/S17030
700 1 _aBiagini, Francesca.
700 1 _aKauermann, Göran.
700 1 _aMeyer-Brandis, Thilo.
856 4 0 _uhttps://doi.org/10.1007/978-3-030-26814-5
912 _aZDB-2-SMA
912 _aZDB-2-SXMS
942 _cEBK
999 _c206058
_d206058