Discrete Choice Methods with Simulation

Train, Kenneth E.

Published by Cambridge University Press
ISBN 10: 0521747384 / ISBN 13: 9780521747387
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2009. 2nd Edition. Paperback. This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Num Pages: 400 pages, 46 b/w illus. 17 tables. BIC Classification: GPQ; KCH. Category: (P) Professional & Vocational. Dimension: 228 x 152 x 22. Weight in Grams: 610. 408 pages, 46 b/w illus. 17 tables. This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. Cateogry: (P) Professional & Vocational. BIC Classification: GPQ; KCH. Dimension: 228 x 152 x 22. Weight: 538. . . . . . Books ship from the US and Ireland. Bookseller Inventory #

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Synopsis: 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 stimulated 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. The second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing.

Book Description: This book describes the new generation of discrete choice methods, focusing on the many advances that are made possible by simulation. 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.

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Title: Discrete Choice Methods with Simulation
Publisher: Cambridge University Press
Book Condition: New

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Kenneth E. Train
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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2009. Paperback. Book Condition: New. 2nd Revised edition. Language: English . Brand New Book. 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. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing. Bookseller Inventory # AAZ9780521747387

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Book Description CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2009. Paperback. Book Condition: New. 2nd Revised edition. Language: English . Brand New Book. 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. Recent advances in Bayesian procedures are explored, including the use of the Metropolis-Hastings algorithm and its variant Gibbs sampling. This second edition adds chapters on endogeneity and expectation-maximization (EM) algorithms. No other book incorporates all these fields, which have arisen in the past 25 years. The procedures are applicable in many fields, including energy, transportation, environmental studies, health, labor, and marketing. Bookseller Inventory # AAZ9780521747387

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Book Description Cambridge University Press, 2009. Paperback. Book Condition: Brand New. 2nd edition. 400 pages. 8.90x5.90x1.00 inches. In Stock. Bookseller Inventory # __0521747384

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