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 …

We propose a probabilistic framework for the treatment of “don't know” responses in surveys
aimed at investigating human perceptions through expressed ratings. The rationale behind …

We design a probability distribution for ordinal data by modeling the process generating
data, which is assumed to rely only on order comparisons between categories. Contrariwise …

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 CUB models the uncertainty of choice is explicitly modelled as a Combination of discrete
Uniform and shifted Binomial random variables. The basic concept to model the response as …

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 …

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 …

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 …