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 China's Emerging Technological Edge by Kenneth E. Train
Cover of the book Risk and Precaution by Kenneth E. Train
Cover of the book Incentives for Global Public Health by Kenneth E. Train
Cover of the book Young Thomas More and the Arts of Liberty by Kenneth E. Train
Cover of the book Vygotsky and Education by Kenneth E. Train
Cover of the book Information Theory by Kenneth E. Train
Cover of the book Recombinant Antibodies for Immunotherapy by Kenneth E. Train
Cover of the book The Social Psychology of Perceiving Others Accurately by Kenneth E. Train
Cover of the book Office-Based Cosmetic Procedures and Techniques by Kenneth E. Train
Cover of the book Dense Sphere Packings by Kenneth E. Train
Cover of the book Epidemics in Modern Asia by Kenneth E. Train
Cover of the book Berkeley's A Treatise Concerning the Principles of Human Knowledge by Kenneth E. Train
Cover of the book Computation, Proof, Machine by Kenneth E. Train
Cover of the book Innovations in Sustainability by Kenneth E. Train
Cover of the book Core Topics in Vascular Anaesthesia 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