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

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...

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Veröffentlicht in:	Statistical methods & applications Jg. 28; H. 3; S. 389 - 435
Hauptverfasser:	Piccolo, Domenico, Simone, Rosaria
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Berlin/Heidelberg Springer Berlin Heidelberg 01.09.2019 Springer Nature B.V
Schlagworte:	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
ISSN:	1618-2510, 1613-981X
Online-Zugang:	Volltext
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