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/she 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 was published in an international journal in 2018 and leads to a keynote as an invited speaker to the 12th Scientific Meeting Classification and Data Analysis Group Cassino (CLADAG 2019) in Italy [41].

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