Advanced Random Regret Minimization Models

Sander van Cranenburgh - Associate Professor Delft University of Technology

Human choice behaviour is predictably irrational - Dan Ariely -

Random Regret Minimization models aim to add insights from behavioural psychology into the econometric framework of discrete choice modelling

Which things will you find on this page?

In the ever-changing world of academic research, exciting new models and techniques regularly come to light, offering tremendous potential for both researchers and practitioners. Yet, the task of coding and implementing these can be daunting, even for the most passionate minds. That's where we step in to make things smoother.

RRM models Find theoretical concepts for models such as P-RRM, μRRM, G-RRM and many more. We have made an summary of the formulations for you to use before you start using these models without complications

Ready to use code Find code compatible with widely used software packages in the community such as PANDAS BIOGEME, Apollo R, PYTHON BIOGEME, BISON BIOGEME, MATLAB and LatentGOLD CHOICE.

More methodology Find advanced techniques for optimising experimental designs, varying the profundity of regretregret and robustness of results with omitted results.

Get in touch

Delft, The Netherlands

Jaffalaan 5

S.vanCranenburgh@tudelft.nl

+31 15 27 86957