Discrete Choice Methods with Simulation
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Summary
Discrete Choice Methods with Simulation by Kenneth Train has been available in the second edition since 2009 and contains two additional chapters, one on endogenous regressors and one on the expectation–maximization (EM) algorithm.
- Type
- article
- Published
- 2016-02-06
- Cited by
- 4,865
- References
- 143
- Access
- Open access
- OpenAlex
- https://openalex.org/W2277429884
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:155207994
Keywords
Computer science, Download, Discrete choice, Operations research, Econometrics
References
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- Discrete Choice Methods with Simulation by Kenneth E. Train
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- Spatial interaction theory and planning models
- A Simple Consistent Non-parametric Estimator of the Regression Function in a Truncated Sample
- Estimation Of Actual Response Coefficients In The Hildreth-Houck Random Coefficient Model
- Measuring Market Power in the Ready-to-Eat Cereal Industry
- A computationally practical simulation estimator for panel data, with applications to labor supply and real wage movement over the business cycle
- Fixed and Random Effects in Nonlinear Models
- Conditional logit analysis of qualitative choice behavior
- A CONDITIONAL PROBIT MODEL FOR QUALITATIVE CHOICE: DISCRETE DECISIONS RECOGNIZING INTERDEPENDENCE AND HETEROGENEOUS PREFERENCES'
- The Impact of Physician Preferences and Patient Habits on the Diffusion of New Drugs
- The method of simulated scores for the estimation of LDV models
- A Factor-Analytic Probit Model for Representing the Market Structure in Panel Data
- The Mixed Logit model: The state of practice
- Simulation-based inference: A survey with special reference to panel data models
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