An alternative approach has been proposed for the analysis and the modelling of ordinal data: it is based on the psychological process by which a respondent expresses his/her evaluation about the item with an inherent indecision. This class of models has been developed with many variants and it is now indicated as CUB models. The purpose of this paper is to introduce users to the version 4.0 of a program, written in the R statistical environment, to make effective applications of CUB models and variants by exploiting their capabilities both from computational and graphical points of view. After a specification of the different structures, the basic commands are presented with some examples. Generalizations and extensions of the standard mod...
estimate a CUB models within the framework of tree based methods in order to provide a tool for gro...
CUB models represent a new approach for the analysis of categorical ordinal data. The relevant domai...
CUB models represent a new approach for the analysis of categorical ordinal data fitted by maximum l...
An alternative approach has been proposed for the analysis and the modelling of ordinal data: it is ...
The class of CUB models is commonly used by practitioners to model ordinal data, in this paper we pr...
UB models are a class of mixture distributions for analyzing ordinal responses in the form of ratin...
UB models are a class of mixture distributions for analyzing ordinal responses in the form of ratin...
This paper discusses a general framework for the analysis of rating and preference data that is root...
This paper discusses a general framework for the analysis of rating and preference data that is root...
This paper discusses a general framework for the analysis of rating and preference data that is root...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...
In this paper we discuss the article “The class of CUB models: statistical foundations, inferential ...
The CUB model is a class of model for ordinal data obtained as a mixture distribution. It is adopted...
CUB models represent a new approach for the analysis of categorical ordinal data. The relevant domai...
estimate a CUB models within the framework of tree based methods in order to provide a tool for gro...
CUB models represent a new approach for the analysis of categorical ordinal data. The relevant domai...
CUB models represent a new approach for the analysis of categorical ordinal data fitted by maximum l...
An alternative approach has been proposed for the analysis and the modelling of ordinal data: it is ...
The class of CUB models is commonly used by practitioners to model ordinal data, in this paper we pr...
UB models are a class of mixture distributions for analyzing ordinal responses in the form of ratin...
UB models are a class of mixture distributions for analyzing ordinal responses in the form of ratin...
This paper discusses a general framework for the analysis of rating and preference data that is root...
This paper discusses a general framework for the analysis of rating and preference data that is root...
This paper discusses a general framework for the analysis of rating and preference data that is root...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...
A mixture model for ordinal data modelling (denoted CUB) has been recently proposed in literature. S...
In this paper we discuss the article “The class of CUB models: statistical foundations, inferential ...
The CUB model is a class of model for ordinal data obtained as a mixture distribution. It is adopted...
CUB models represent a new approach for the analysis of categorical ordinal data. The relevant domai...
estimate a CUB models within the framework of tree based methods in order to provide a tool for gro...
CUB models represent a new approach for the analysis of categorical ordinal data. The relevant domai...
CUB models represent a new approach for the analysis of categorical ordinal data fitted by maximum l...