000 02245nam a22003498i 4500
001 CR9781316779422
003 UkCbUP
005 20240919172051.0
006 m|||||o||d||||||||
007 cr||||||||||||
008 160321s2017||||enk o ||1 0|eng|d
020 _a9781316779422 (ebook)
020 _z9781107172876 (hardback)
020 _z9781316625064 (paperback)
040 _aUkCbUP
_beng
_erda
_cUkCbUP
050 0 0 _aQA166.17
_b.H64 2017
082 0 0 _a511/.5
_223
100 1 _aHofstad, Remco van der,
_eauthor.
245 1 0 _aRandom graphs and complex networks.
_nVolume 1 /
_cRemco van der Hofstad, Technische Universiteit Eindhoven.
264 1 _aCambridge :
_bCambridge University Press,
_c2017.
300 _a1 online resource (xvi, 321 pages) :
_bdigital, PDF file(s).
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
490 1 _aCambridge series in statistical and probabilistic mathematics ;
_v43
500 _aTitle from publisher's bibliographic system (viewed on 31 Jan 2017).
520 _aThis rigorous introduction to network science presents random graphs as models for real-world networks. Such networks have distinctive empirical properties and a wealth of new models have emerged to capture them. Classroom tested for over ten years, this text places recent advances in a unified framework to enable systematic study. Designed for a master's-level course, where students may only have a basic background in probability, the text covers such important preliminaries as convergence of random variables, probabilistic bounds, coupling, martingales, and branching processes. Building on this base - and motivated by many examples of real-world networks, including the Internet, collaboration networks, and the World Wide Web - it focuses on several important models for complex networks and investigates key properties, such as the connectivity of nodes. Numerous exercises allow students to develop intuition and experience in working with the models.
650 0 _aRandom graphs.
830 0 _aCambridge series on statistical and probabilistic mathematics ;
_v43.
856 4 0 _uhttps://doi.org/10.1017/9781316779422
942 _2ddc
_cEB
999 _c9802
_d9802