Discrete Choice Methods with Simulation

Business & Finance, Economics, Econometrics, Nonfiction, Science & Nature, Mathematics
Cover of the book Discrete Choice Methods with Simulation by Kenneth E. Train, Cambridge University Press
View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart
Author: Kenneth E. Train ISBN: 9781107713420
Publisher: Cambridge University Press Publication: June 30, 2009
Imprint: Cambridge University Press Language: English
Author: Kenneth E. Train
ISBN: 9781107713420
Publisher: Cambridge University Press
Publication: June 30, 2009
Imprint: Cambridge University Press
Language: English

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.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

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.

More books from Cambridge University Press

Cover of the book A User's Guide to Measure Theoretic Probability by Kenneth E. Train
Cover of the book The African Court of Justice and Human and Peoples' Rights in Context by Kenneth E. Train
Cover of the book How Americans Make Race by Kenneth E. Train
Cover of the book Holy Scripture by Kenneth E. Train
Cover of the book Rebel Governance in Civil War by Kenneth E. Train
Cover of the book Geometry, Topology, and Dynamics in Negative Curvature by Kenneth E. Train
Cover of the book A Concise History of Japan by Kenneth E. Train
Cover of the book The Doctrine of Salvation in the First Letter of Peter by Kenneth E. Train
Cover of the book The Role of the Public Bureaucracy in Policy Implementation in Five ASEAN Countries by Kenneth E. Train
Cover of the book Fault Lines of International Legitimacy by Kenneth E. Train
Cover of the book Magnetohydrodynamics of the Sun by Kenneth E. Train
Cover of the book British Political Culture and the Idea of ‘Public Opinion', 1867–1914 by Kenneth E. Train
Cover of the book Violence and the Civilising Process in Cambodia by Kenneth E. Train
Cover of the book Law, Tropical Forests and Carbon by Kenneth E. Train
Cover of the book Modernism and the Reinvention of Decadence by Kenneth E. Train
We use our own "cookies" and third party cookies to improve services and to see statistical information. By using this website, you agree to our Privacy Policy