000			02300nam a22003378i 4500
001			CR9780511753930
003			UkCbUP
005			20200124160258.0
006			m|||||o||d||||||||
007			cr||||||||||||
008			141103s2003||||enk o ||1 0|eng|d
020			_a9780511753930 (ebook)
020			_z9780521816960 (hardback)
020			_z9780521017152 (paperback)
040			_aUkCbUP _beng _erda _cUkCbUP
050	0	0	_aHD30.23 _b.T725 2003
082	0	0	_a003/.56 _221
100	1		_aTrain, Kenneth, _eauthor.
245	1	0	_aDiscrete choice methods with simulation / _cKenneth E. Train.
264		1	_aCambridge : _bCambridge University Press, _c2003.
300			_a1 online resource (vii, 334 pages) : _bdigital, PDF file(s).
336			_atext _btxt _2rdacontent
337			_acomputer _bc _2rdamedia
338			_aonline resource _bcr _2rdacarrier
500			_aTitle from publisher's bibliographic system (viewed on 05 Oct 2015).
520			_aThis book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Researchers use these statistical methods to examine the choices that consumers, households, firms, and other agents make. Each of the major models is covered: logit, generalized extreme value, or GEV (including nested and cross-nested logits), probit, and mixed logit, plus a variety of specifications that build on these basics. Simulation-assisted estimation procedures are investigated and compared, including maximum simulated likelihood, method of simulated moments, and method of simulated scores. Procedures for drawing from densities are described, including variance reduction techniques such as anithetics and Halton draws. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. No other book incorporates all these fields, which have arisen in the past 20 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.
650		0	_aDecision making _xSimulation methods.
650		0	_aConsumers' preferences _xSimulation methods.
776	0	8	_iPrint version: _z9780521816960
856	4	0	_uhttps://doi.org/10.1017/CBO9780511753930
999			_c520116 _d520114