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randregret: A command for fitting random regret minimization models using Stata

Author

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  • Alvaro Gutierrez Vargas
  • Michel Meulders
  • Martina Vandebroek

Abstract

In this article, we describe the randregret command, which imple-ments a variety of Random Regret Minimization (RRM) models. The command allows the user to apply the classic RRM model introduced in Chorus (2010, Eu-ropean Journal of Transport and Infrastructure Research 10: 181-196), the Gener-alized RRM model introduced in Chorus (2014, Transportation Research Part B: Methodological 68: 224-238), and also the µRRM and Pure RRM models, both introduced in van Cranenburgh et al. (2015, Transportation Research Part A: Pol-icy and Practice 74: 91-109). We illustrate the usage of the randregret command using stated choice data on route preferences. The command offers robust and cluster standard error correction using analytical expressions of the scores func-tions. It also offers likelihood ratio tests that can be used to assess the relevance of a given model speciï¬cation. Finally, users can obtain the predicted probabilities from each model using the randregretpred command.

Suggested Citation

  • Alvaro Gutierrez Vargas & Michel Meulders & Martina Vandebroek, 2021. "randregret: A command for fitting random regret minimization models using Stata," Working Papers of Department of Decision Sciences and Information Management, Leuven 664773, KU Leuven, Faculty of Economics and Business (FEB), Department of Decision Sciences and Information Management, Leuven.
    • Handle: RePEc:ete:kbiper:664773
    Note: paper number KBI_2006
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    Keywords

    randregret; randregret pure; randregretpred; discrete choice models; semi-compensatory behavior; random utility maximization; random regret mini-mization;
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