Generalized Random Utility Models with Multiple Types Generalized Random Utility Models with Multiple Types
Paper summary This paper is related with the problem of demand estimation in multi-heterogeneous agents, specifically, to classify agents and estimate preferences of each agent type using agents’ ranking data of different alternatives. The problem is important since it has great practical value in studying underlying preference distributions of multiple agents. To tackle the problem, the authors introduce generalized random utility models (GRUM), provide RJMCMC algorithms for parameter estimation in GRUM and theoretically establish conditions for identifiability for the model. Experimental results on both synthetic and real dataset show the model’s effectiveness.

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