Ordinal models can be seen as being composed from simpler, in particular binary models.
This view on ordinal models allows to derive a taxonomy of models that includes basic …

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 …

In this article we introduce a probability distribution generated by a mixture of discrete
random variables to capture uncertainty, feeling, and overdispersion, possibly present in …

Ordinal measurements as ratings, preference and evaluation data are very common in
applied disciplines, and their analysis requires a proper modelling approach for …

In several applied disciplines, as Economics, Marketing, Business, Sociology, Psychology,
Political science, Environmental research and Medicine, it is common to collect data in the …

In dealing with veracity of data analytics, fuzzy methods are more and more relying on
probabilistic and statistical techniques to underpin their applicability. Conversely, standard …

Literature on the models for ordinal variables grew very fast in the last decades and several
proposals have been advanced when ordered data are expression of ratings, preferences …

Mixture models for ordinal responses in the tradition of cub models use the uniform
distribution to account for uncertainty of respondents. A model is proposed that uses more …

The paper is framed within the literature around Louis' identity for the observed information
matrix in incomplete data problems, with a focus on the implied acceleration of maximum …

A statistical framework for modelling subjective perceptions expressed through ratings is
presented. The paper deals with the relationships between personal covariates and self …