Latent class analysis can be viewed as a special case of model–based clustering for
multivariate discrete data. It is assumed that each observation comes from one of a number …

In several empirical applications analyzing customer-by-product choice data, it may be
relevant to partition individuals having similar purchase behavior in homogeneous …

Clustering seeks to identify a finite set of clusters to describe data. Cluster analysis is
partitioning similar objects into meaningful classes, when both the number of classes and …

The topic of market segmentation is still one of the most pervasive in marketing. Among
clustering techniques, finite mixture models have gained recognition as a method of …

Three-way data sets occur when various attributes are measured for a set of observational
units in different situations. Examples are genotype by environment by attribute data …

The objective of the present work is to highlight the importance of multidimensional
categorical models applied to marketing strategies, with particular regard to customer …

Discovering the preferences and the behaviour of consumers is a key challenge in
marketing. Information about such topics can be gathered through surveys in which the …

In social and economic studies many of the collected variables are measured on a nominal
scale, often with a large number of categories. The definition of categories can be …

When using mixture models, researchers may investigate the associations between cluster
membership and covariates by introducing these variables in a (logistic) regression model …

The present work proposes a method based on CLV (Clustering around Latent Variables)
for identifying groups of consumers in L-shape data. This kind of datastructure is very …