Simulation estimation of mixed discrete choice models using randomized and scrambled Halton sequences
AbstractThe use of simulation techniques has been increasing in recent years in the transportation and related fields to accommodate flexible and behaviorally realistic structures for analysis of decision processes. This paper proposes a randomized and scrambled version of the Halton sequence for use in simulation estimation of discrete choice models. The scrambling of the Halton sequence is motivated by the rapid deterioration of the standard Halton sequence's coverage of the integration domain in high dimensions of integration. The randomization of the sequence is motivated from a need to statistically compute the simulation variance of model parameters. The resulting hybrid sequence combines the good coverage property of quasi-Monte Carlo sequences with the ease of estimating simulation error using traditional Monte Carlo methods. The paper develops an evaluation framework for assessing the performance of the traditional pseudo-random sequence, the standard Halton sequence, and the scrambled Halton sequence. The results of computational experiments indicate that the scrambled Halton sequence performs better than the standard Halton sequence and the traditional pseudo-random sequence for simulation estimation of models with high dimensionality of integration.
Download InfoIf you experience problems downloading a file, check if you have the proper application to view it first. In case of further problems read the IDEAS help page. Note that these files are not on the IDEAS site. Please be patient as the files may be large.
Bibliographic InfoArticle provided by Elsevier in its journal Transportation Research Part B: Methodological.
Volume (Year): 37 (2003)
Issue (Month): 9 (November)
Contact details of provider:
Web page: http://www.elsevier.com/wps/find/journaldescription.cws_home/548/description#description
Please report citation or reference errors to , or , if you are the registered author of the cited work, log in to your RePEc Author Service profile, click on "citations" and make appropriate adjustments.:
- J. A. Hausman & D. A. Wise, 1976.
"A Conditional Profit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences,"
173, Massachusetts Institute of Technology (MIT), Department of Economics.
- Hausman, Jerry A & Wise, David A, 1978. "A Conditional Probit Model for Qualitative Choice: Discrete Decisions Recognizing Interdependence and Heterogeneous Preferences," Econometrica, Econometric Society, vol. 46(2), pages 403-26, March.
- Bhat, Chandra R., 2001. "Quasi-random maximum simulated likelihood estimation of the mixed multinomial logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 677-693, August.
- Kenneth Train, .
"Simulation Methods for Probit and Related Models Based on Convenient Error Partitioning,"
_009, University of California at Berkeley, Econometrics Laboratory Software Archive.
- Kenneth E. Train, 1996. "Simulation Methods for Probit and Related Models Based on Convenient Error Partitioning," Econometrics 9605001, EconWPA.
- Train, Kenneth E., 1995. "Simulation Methods for Probit and Related Models Based on Convenient Error Partitioning," Department of Economics, Working Paper Series qt94h8x4gd, Department of Economics, Institute for Business and Economic Research, UC Berkeley.
- Kenneth E. Train., 1995. "Simulation Methods for Probit and Related Models Based on Convenient Error Partitioning," Economics Working Papers 95-237, University of California at Berkeley.
- Hajivassiliou, Vassilis & McFadden, Daniel & Ruud, Paul, 1996.
"Simulation of multivariate normal rectangle probabilities and their derivatives theoretical and computational results,"
Journal of Econometrics,
Elsevier, vol. 72(1-2), pages 85-134.
- Vassilis A. Hajivassiliou & Daniel L. McFadden & Paul Ruud, 1993. "Simulation of Multivariate Normal Rectangle Probabilities and their Derivatives: Theoretical and Computational Results," Working Papers _024, Yale University.
- Bhat, Chandra R., 1995. "A heteroscedastic extreme value model of intercity travel mode choice," Transportation Research Part B: Methodological, Elsevier, vol. 29(6), pages 471-483, December.
This item has more than 25 citations. To prevent cluttering this page, these citations are listed on a separate page. reading list or among the top items on IDEAS.Access and download statisticsgeneral information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Zhang, Lei).
If references are entirely missing, you can add them using this form.