  Any limiting point process for the time normalized exceedances of high levels
by a stationary sequence is necessarily compound Poisson under appropriate long
range dependence conditions. Typically exceedances appear in clusters. The
underlying Poisson points represent the cluster positions and the
multiplicities correspond to the cluster sizes. In the present paper we
introduce estimators of the limiting cluster size probabilities, which are
constructed through a recursive algorithm. We derive estimators of the extremal
index which plays a key role in determining the intensity of cluster positions.
We study the asymptotic properties of the estimators and investigate their
finite sample behavior on simulated data.
