  In this paper an approach to modelling nonstationary binary sequences, i.e.,
predicting the probability of upcoming symbols, is presented. After studying
the prediction model we evaluate its performance in two non-artificial test
cases. First the model is compared to the Laplace and Krichevsky-Trofimov
estimators. Secondly a statistical ensemble model for compressing
Burrows-Wheeler-Transform output is worked out and evaluated. A systematic
approach to the parameter optimization of an individual model and the ensemble
model is stated.
