Discrete Choice Methods with Simulation

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Bibliographic Details
Title: Discrete Choice Methods with Simulation
Description: 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.
Authors: Kenneth E. Train
Resource Type: eBook.
Subjects: Decision making--Simulation methods, Consumers' preferences--Simulation methods
Categories: COMPUTERS / Cybernetics
Database: eBook Collection (EBSCOhost)
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  – Type: ebook-pdf
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  Availability: 0
Header DbId: nlebk
DbLabel: eBook Collection (EBSCOhost)
An: 125104
RelevancyScore: 985
AccessLevel: 6
PubType: eBook
PubTypeId: ebook
PreciseRelevancyScore: 985.343994140625
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  Data: 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.
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      – Code: 003.56
        Scheme: ddc
        Type: prePub
    Languages:
      – Code: eng
        Text: English
    Subjects:
      – SubjectFull: Decision making--Simulation methods
        Type: general
      – SubjectFull: Consumers' preferences--Simulation methods
        Type: general
    Titles:
      – TitleFull: Discrete Choice Methods with Simulation
        Type: main
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      – PersonEntity:
          Name:
            NameFull: Kenneth E. Train
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            NameFull: Kenneth E. Train
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          Dates:
            – D: 01
              M: 01
              Type: published
              Y: 2003
            – D: 04
              M: 02
              Type: profile
              Y: 2014
          Identifiers:
            – Type: isbn-print
              Value: 9780521816960
            – Type: isbn-electronic
              Value: 9780511078347
          Titles:
            – TitleFull: Discrete Choice Methods with Simulation
              Type: main
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