  There are two main objectives of this paper. The first is to present a
statistical framework for models with context specific independence structures,
i.e., conditional independences holding only for sepcific values of the
conditioning variables. This framework is constituted by the class of split
models. Split models are extension of graphical models for contigency tables
and allow for a more sophisticiated modelling than graphical models. The
treatment of split models include estimation, representation and a Markov
property for reading off those independencies holding in a specific context.
The second objective is to present a software package named YGGDRASIL which is
designed for statistical inference in split models, i.e., for learning such
models on the basis of data.
