Section: New Results

Axis 1: Data Units Selection in Statistics

Participant : Christophe Biernacki.

Usually, the data unit definition is fixed by the practitioner but it can happen that he/her hesitates between several data unit options. In this context, it is highlighted that it is possible to embed data unit selection into a classical model selection principle. The problem is introduced in a regression context before to focus on the model-based clustering and co-clustering context, for data of different kinds (continuous, count, categorical). This work is now published in an international journal [12].

An extension of this work has been also presented to an international workshop.The idea is to use the data units principle as a way for (co-)clustering model enlargement.

It is a joint work with Alexandre Lourme from University of Bordeaux.