Classification methods for random utility models with i.i.d. disturbances under the most probable alternative rule
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References listed on IDEAS
- Walker, Joan & Ben-Akiva, Moshe, 2002. "Generalized random utility model," Mathematical Social Sciences, Elsevier, vol. 43(3), pages 303-343, July.
- Hensher, David A. & Greene, William H., 2002. "Specification and estimation of the nested logit model: alternative normalisations," Transportation Research Part B: Methodological, Elsevier, vol. 36(1), pages 1-17, January.
- Provencher, Bill & Bishop, R.C.Richard C., 2004. "Does accounting for preference heterogeneity improve the forecasting of a random utility model? A case study," Journal of Environmental Economics and Management, Elsevier, vol. 48(1), pages 793-810, July.
- Manski, Charles F. & Thompson, T. Scott, 1986. "Operational characteristics of maximum score estimation," Journal of Econometrics, Elsevier, vol. 32(1), pages 85-108, June.
- Manrai, Ajay K., 1995. "Mathematical models of brand choice behavior," European Journal of Operational Research, Elsevier, vol. 82(1), pages 1-17, April.
- Wen, Chieh-Hua & Koppelman, Frank S., 2001. "The generalized nested logit model," Transportation Research Part B: Methodological, Elsevier, vol. 35(7), pages 627-641, August.
- Benati, Stefano & Hansen, Pierre, 2002. "The maximum capture problem with random utilities: Problem formulation and algorithms," European Journal of Operational Research, Elsevier, vol. 143(3), pages 518-530, December.
- Munizaga, Marcela A. & Heydecker, Benjamin G. & Ortúzar, Juan de Dios, 2000. "Representation of heteroskedasticity in discrete choice models," Transportation Research Part B: Methodological, Elsevier, vol. 34(3), pages 219-240, April.
- Baltas, George, 2004. "A model for multiple brand choice," European Journal of Operational Research, Elsevier, vol. 154(1), pages 144-149, April.
- Manski, Charles F., 1975. "Maximum score estimation of the stochastic utility model of choice," Journal of Econometrics, Elsevier, vol. 3(3), pages 205-228, August.
- David Hensher & William Greene, 2003. "The Mixed Logit model: The state of practice," Transportation, Springer, vol. 30(2), pages 133-176, May.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- Kalouptsidis, N. & Psaraki, V., 2010. "Approximations of choice probabilities in mixed logit models," European Journal of Operational Research, Elsevier, vol. 200(2), pages 529-535, January.
- Pancras, Joseph, 2011. "The nested consideration model: Investigating dynamic store consideration sets and store competition," European Journal of Operational Research, Elsevier, vol. 214(2), pages 340-347, October.
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