Growing happiness: a model-based tree

Tree based methods in statistics are gaining a renewed interest in the Big Data era since they entail effective interpretation of results. In this setting, we apply a model-based technique to build trees for ordinal responses relying on a class of mixture models whose characteristic feature is the probabilistic specification of uncertainty. An application to the perception of happiness shows that the integration of tree methods with the chosen modelling boosts cluster analysis of respondents.