  This paper proposes a new method to combine several densities such that each
density dominates a separate part of a joint distribution. The method is fully
unsupervised, i.e. the parameters in the densities and the thresholds are
simultaneously estimated. The approach uses cdf functions in the mixing. This
makes it easy to estimate parameters and the resulting density is smooth. Our
method may be used both when the tails are heavier and lighter than the rest of
the distribution. The presented model is compared with other published models
and a very simple model using a univariate transformation.
