Acceso usuarios
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 gen- eralized RRM model introduced in Chorus (2014, Transportation Research, Part B 68: 224–238), and also the μRRM and pure RRM models, both introduced in van Cranenburgh, Guevara, and Chorus (2015, Transportation Research, Part A 74: 91–109). We illustrate the use of the randregret command by using stated choice data on route preferences. The command offers robust and cluster standard-error correction using analytical expressions of the score functions. It also offers likelihood-ratio tests that can be used to assess the relevance of a given model specification. Finally, users can obtain the predicted probabilities from each model by using the randregretpred command
