Fitting mixed random regret minimization models using maximum simulated likelihood

Ziyue Zhu*, Alvaro A. Gutierrez-Vargas, Martina Vandebroek

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

In this article, we describe the mixrandregret command, which extends the randregret command introduced in Guti & eacute;rrez-Vargas, Meulders, and Vandebroek (2021, Stata Journal 21: 626-658) by allowing random coefficients in random regret minimization models. The newly developed mixrandregret command 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.
Original languageEnglish
Pages (from-to)250-272
Number of pages23
JournalStata Journal
Volume24
Issue number2
DOIs
Publication statusPublished - 1 Jun 2024

Keywords

  • st0746
  • mixrandregret
  • mixrpred
  • mixrbeta
  • discrete choice models
  • random regret model
  • logit model
  • random coefficients
  • UTILITY MAXIMIZATION
  • LOGIT-MODELS
  • CHOICE
  • COMMAND
  • PREFERENCES
  • ROBUSTNESS

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