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Fitting mixed random regret minimization models using maximum simulated likelihood

Author

Listed:
  • Ziyue Zhu

    (Maastricht University)

  • Álvaro A. Gutiérrez-Vargas

    (KU Leuven)

  • Martina Vandebroek

    (KU Leuven)

Abstract

In this article, we describe the mixrandregret command, which ex- tends the randregret command introduced in Gutiérrez-Vargas, Meulders, and Vandebroek (2021, Stata Journal 21: 626–658) by allowing random coefficients in random regret minimization models. The newly developed mixrandregret com- mand allows the user to specify a combination of fixed and random coefficients in the regret function of the classical random regret minimization model introduced in Chorus (2010, European Journal of Transport and Infrastructure Research 10: 181–196). In addition, the user can specify normal and lognormal distributions for the random coefficients using the appropriate command’s options. The models are fit by maximum simulated likelihood estimation using numerical integration to approximate the choice probabilities.

Suggested Citation

  • Ziyue Zhu & Álvaro A. Gutiérrez-Vargas & Martina Vandebroek, 2024. "Fitting mixed random regret minimization models using maximum simulated likelihood," Stata Journal, StataCorp LP, vol. 24(2), pages 250-272, June.
    • Handle: RePEc:tsj:stataj:v:24:y:2024:i:2:p:250-272
    DOI: 10.1177/1536867X241257802
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