000			02038nam a22003497a 4500
001			sulb-eb0015385
003			BD-SySUS
005			20160405134433.0
008			101117s2012||||enk o ||1 0|eng|d
020			_a9780511894701 (ebook)
020			_z9780521193566 (hardback)
020			_z9780521141383 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aHM741 _b.E96 2013
082	0	0	_a302.3 _223
245	0	0	_aExponential Random Graph Models for Social Networks : _bTheory, Methods, and Applications / _cedited by Dean Lusher, Johan Koskinen, Garry Robins.
264		1	_aCambridge : _bCambridge University Press, _c2012.
300			_a1 online resource (360 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
490	0		_aStructural Analysis in the Social Sciences ; _v35
500			_aTitle from publisher's bibliographic system (viewed on 04 Apr 2016).
520			_aExponential random graph models (ERGMs) are increasingly applied to observed network data and are central to understanding social structure and network processes. The chapters in this edited volume provide a self-contained, exhaustive account of the theoretical and methodological underpinnings of ERGMs, including models for univariate, multivariate, bipartite, longitudinal and social-influence type ERGMs. Each method is applied in individual case studies illustrating how social science theories may be examined empirically using ERGMs. The authors supply the reader with sufficient detail to specify ERGMs, fit them to data with any of the available software packages and interpret the results.
700	1		_aLusher, Dean, _eeditor.
700	1		_aKoskinen, Johan, _eeditor.
700	1		_aRobins, Garry, _eeditor.
776	0	8	_iPrint version: _z9780521193566
830		0	_aStructural Analysis in the Social Sciences ; _v35.
856	4	0	_uhttp://dx.doi.org/10.1017/CBO9780511894701
942			_2Dewey Decimal Classification _ceBooks
999			_c37229 _d37229