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Recent developments in discrete choice model formulation, estimation, and inference

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  • Bhat, Chandra R.

Abstract

The developments in discrete choice formulation, estimation and inference techniques have been fast and furious over the past few years. This special issue of Transportation Research Part B is a compilation of some of the cutting-edge research in the field.

Suggested Citation

  • Bhat, Chandra R., 2012. "Recent developments in discrete choice model formulation, estimation, and inference," Transportation Research Part B: Methodological, Elsevier, vol. 46(2), pages 273-275.
    • Handle: RePEc:eee:transb:v:46:y:2012:i:2:p:273-275
    DOI: 10.1016/j.trb.2011.10.007
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    References listed on IDEAS

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    1. 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.
    2. Matthew C. Harding & Jerry Hausman, 2007. "Using A Laplace Approximation To Estimate The Random Coefficients Logit Model By Nonlinear Least Squares," International Economic Review, Department of Economics, University of Pennsylvania and Osaka University Institute of Social and Economic Research Association, vol. 48(4), pages 1311-1328, November.
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    1. Crabbe, Marjolein & Akinc, Deniz & Vandebroek, Martina, 2014. "Fast algorithms to generate individualized designs for the mixed logit choice model," Transportation Research Part B: Methodological, Elsevier, vol. 60(C), pages 1-15.

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