K. Train (Kenneth)
http://repub.eur.nl/ppl/5918/
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http://repub.eur.nl/
RePub, Erasmus University RepositoryRisk, uncertainty and discrete choice models
http://repub.eur.nl/pub/14515/
Mon, 01 Dec 2008 00:00:01 GMT<div>A. de Palma</div><div>M. Ben-Akiva</div><div>D. Brownstone</div><div>C. Hol</div><div>T. Magnac</div><div>D. McFadden</div><div>P. Moffatt</div><div>N. Picard</div><div>K. Train</div><div>P.P. Wakker</div><div>J. Walker</div>
This paper examines the cross-fertilizations of random utility models with the study of decision making under risk and uncertainty. We start with a description of the expected utility (EU) theory and then consider deviations from the standard EU frameworks, involving the Allais paradox and the Ellsberg paradox, inter alia. We then discuss how the resulting non-EU framework can be modeled and estimated within the framework of discrete choices in static and dynamic contexts. Our objectives in addressing risk and ambiguity in individual choice contexts are to understand the decision choice process and to use behavioral information for prediction, prescription, and policy analysis.Quasi-random simulation of discrete choice models
http://repub.eur.nl/pub/1829/
Mon, 20 Dec 2004 00:00:01 GMT<div>Z. Sándor</div><div>K. Train</div>
We describe the properties of (t,m,s)-nets and Halton draws. Four types of (t,m,s)-nets, two types of Halton draws, and independent draws are compared in an application of maximum simulated likelihood estimation of a mixed logit model. All of the quasi-random procedures are found to perform far better than independent draws. The best performance is attained by one of the (t,m,s)-nets. The properties of the nets imply that two of them should outperform the other two, and our results confirm this expectation. The two more-accurate nets perform better than both types of Halton draws, while the two less-accurate nets perform worse than the Halton draws.Quasi-random simulation of discrete choice models
http://repub.eur.nl/pub/57875/
Sat, 01 May 2004 00:00:01 GMT<div>Z. Sándor</div><div>K. Train</div>
We describe the properties of (t,m,s)-nets and Halton draws. Four types of (t,m,s)-nets, two types of Halton draws, and independent draws are compared in an application of maximum simulated likelihood estimation of a mixed logit model. All of the quasi-random procedures are found to perform far better than independent draws. The best performance is attained by one of the (t,m,s)-nets. The properties of the nets imply that two of them should outperform the other two, and our results confirm this expectation. The two more-accurate nets perform better than both types of Halton draws, while the two less-accurate nets perform worse than the Halton draws.