ALICE Statistical Wish-list

A few statistical problems faced by the event reconstruction in ALICE experiment at CERN are discussed in this paper. We outline several ad-hoc extensions of traditional Kalman- lter track nding which seem to increase the quality of tracks reconstructed in high multiplicity events anticipated for Pb– Pb collisions at LHC. These extensions, however, need a stricter formulation and justi cation from the theoretical side. The particle identi cation in ALICE is done by combining the information from different detecting systems using a Bayesian method. Having many clear advantages, this approach introduces into the analysis additional complications which are also discussed here.