The relations between automatic clustering methods and
inferentiel statistical models have mostely been studied when the data
involves only one set. We propose to study these relations in the case
of data
involving two sets. We shall look at cross clustering methods as
suggested by
Govaert [6]; we show that these methods, like the simple clustering
methods,
can be considered as a clustering approach of a mixture model. We
introduce
the notion of crossed mixture from a concret example and define the
notions of
likelihood and associated clustered likelihood. Then, we study the
relations
which exist between the crossed mixture models and simple models and we
show
that these relations are completely similar to those which exist between
the
crossed clustering methods and simple clustering methods.