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Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation

Discrete Choice Methods with Simulation
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Discrete Choice Methods with Simulation Paperback - 2009 - 2nd Edition

by Kenneth E. Train

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Cambridge University Press, 2009. Paperback. New. 2nd edition. 400 pages. 8.90x5.90x1.00 inches.
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Details

  • Title Discrete Choice Methods with Simulation
  • Author Kenneth E. Train
  • Binding Paperback
  • Edition number 2nd
  • Edition 2
  • Condition New
  • Pages 400
  • Volumes 1
  • Language ENG
  • Publisher Cambridge University Press, Cambridge
  • Publication date 2009
  • Illustrated Yes
  • Features Bibliography, Illustrated, Index
  • Bookseller's Inventory # x-0521747384
  • ISBN 9780521747387 / 0521747384
  • Weight 1.2 lbs (0.54 kg)
  • Dimensions 9 x 6 x 0.9 in (22.86 x 15.24 x 2.29 cm)
  • Category Business / Economics / Finance
  • Library of Congress subjects Decision making - Simulation methods, Consumers' preferences - Simulation methods
  • Library of Congress Catalogue Number 2009020438
  • Dewey Decimal Code 003.56
  • Quantity available 2

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From the publisher

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.

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