  This paper introduces a convenient strategy for coding and predicting
sequences of independent, identically distributed random variables generated
from a large alphabet of size $m$. In particular, the size of the sample is
allowed to be variable. The employment of a Poisson model and tilting method
simplifies the implementation and analysis through independence. The resulting
strategy is optimal within the class of distributions satisfying a moment
condition, and is close to optimal for the class of all i.i.d distributions on
strings of a given length. Moreover, the method can be used to code and predict
strings with a condition on the tail of the ordered counts. It can also be
applied to distributions in an envelope class.
