The class of cub models: statistical foundations, inferential issues and empirical evidence

• Published in: Statistical methods & applications Vol. 28; no. 3; pp. 389 - 435
• Main Authors: Piccolo, Domenico, Simone, Rosaria
• Format: Journal Article
• Language: English
• Published: Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2019; Springer Nature B.V
• Subjects: Chemistry and Earth Sciences; Computer Science; Economics; Empirical analysis; Finance; Health Sciences; Humanities; Insurance; Law; Management; Mathematics and Statistics; Medicine; Original Paper; Parameterization; Performance prediction; Physics; Random variables; Statistical models; Statistical Theory and Methods; Statistics; Statistics for Business; Statistics for Engineering; Statistics for Life Sciences; Statistics for Social Sciences; Uncertainty; models; Explicative power; Predictability; Data generating process; Ordinal data; Ratings

This paper discusses a general framework for the analysis of rating and preference data that is rooted on a class of mixtures of discrete random variables. These models have been extensively studied and applied in the last 15 years thanks to a flexible and parsimonious parametrization of data genera...