Cumulative and CUB Models for Rating Data: A Comparative Analysis
Cumulative and CUB Models for Rating Data: A Comparative Analysis is a scholarly work, published in 2018 in ''International Statistical Review''. The main subjects of the publication include interpretation, econometrics, mixture model, data mining, artificial intelligence, preference, discrete choice, class, ordinal variable, feature, missing data, machine learning, and computer science. The work proposes a comparative discussion between two statistical frameworks that serve these goals: the established class of cumulative models and a class of mixtures of discrete random variables, denoted asCUBmodels, whose peculiar feature is the specification of an uncertainty component to deal with indecision and heterogeneity.