Print Email Facebook Twitter Sampling of alternatives in random regret minimization models Title Sampling of alternatives in random regret minimization models Author Guevara, C. Chorus, C.G. Ben-Akiva, M.E. Faculty Technology, Policy and Management Department Infrastructures, Systems and Services Date 2013-01-17 Abstract 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. Subject sampling of alternativesrandom regret To reference this document use: http://resolver.tudelft.nl/uuid:3f6df7c8-a220-46a4-9744-9bae83025604 Publisher TRB Source 92nd Annual Meeting Transportation Research Board, Washington, USA, 13-17 January 2013; Authors version Part of collection Institutional Repository Document type conference paper Rights (c) 2013 Guevara, C., Chorus, C.G., Ben-Akiva, M.E. Files PDF 302158.pdf 560.01 KB Close viewer /islandora/object/uuid:3f6df7c8-a220-46a4-9744-9bae83025604/datastream/OBJ/view