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Discrete choice methods with simulat...

Train, Kenneth,

Discrete choice methods with simulation /

Record Type:	Language materials, printed : Monograph/item
[NT 15000414]:	003/.56
Title/Author:	Discrete choice methods with simulation // Kenneth E. Train.
Author:	Train, Kenneth,
Description:	1 online resource (vii, 334 pages) : : digital, PDF file(s).
Notes:	Title from publisher's bibliographic system (viewed on 05 Oct 2015).
Subject:	Decision making - Simulation methods.
Subject:	Consumers' preferences - Simulation methods.
ISBN:	9780511753930 (ebook)
[NT 15000229]:	This 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.
Online resource:	http://dx.doi.org/10.1017/CBO9780511753930

Discrete choice methods with simulation /
Train, Kenneth,

Discrete choice methods with simulation /Kenneth E. Train. - 1 online resource (vii, 334 pages) :digital, PDF file(s).

Title from publisher's bibliographic system (viewed on 05 Oct 2015).

This 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.

ISBN: 9780511753930 (ebook)Subjects--Topical Terms:

613148
Decision making
--Simulation methods.

LC Class. No.: HD30.23 / .T725 2003

Dewey Class. No.: 003/.56

Discrete choice methods with simulation /
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020 $z 9780521816960 (hardback)
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050 0 0 $a HD30.23 $b .T725 2003
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245 1 0 $a Discrete choice methods with simulation / $c Kenneth E. Train.
264 1 $a Cambridge : $b Cambridge University Press, $c 2003.
300 $a 1 online resource (vii, 334 pages) : $b digital, PDF file(s).
336 $a text $b txt $2 rdacontent
337 $a computer $b c $2 rdamedia
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500 $a Title from publisher's bibliographic system (viewed on 05 Oct 2015).
520 $a This 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 $a Decision making $x Simulation methods. $3 613148
650 0 $a Consumers' preferences $x Simulation methods. $3 644061
776 0 8 $i Print version: $z 9780521816960
856 4 0 $u http://dx.doi.org/10.1017/CBO9780511753930

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