Sampling of alternatives in random regret minimization models

Sampling of alternatives in random regret minimization models

Guevara, C.
Chorus, C.G.
Ben-Akiva, M.E.

Technology, Policy and Management

Infrastructures, Systems and Services

2013-01-17

We propose a methodology to achieve consistency, asymptotic normality and efficiency, while sampling alternatives in Random Regret Minimization models. Our method is an extension of previous results for Logit and MEV models. We illustrate the methodology using Monte Carlo experimentation. Experiments show that the proposed methodology is practical, that it outperforms the uncorrected model, and that it yields acceptable results.

sampling of alternatives
random regret

http://resolver.tudelft.nl/uuid:3f6df7c8-a220-46a4-9744-9bae83025604

TRB

92nd Annual Meeting Transportation Research Board, Washington, USA, 13-17 January 2013; Authors version

Institutional Repository

conference paper

(c) 2013 Guevara, C., Chorus, C.G., Ben-Akiva, M.E.