A universal prediction lemma and applications to universal data compression

A universal prediction lemma is derived for the class of conditional probability measures that are limited to conditioning events that occur in the training data. The lemma is then used to derive lower bounds on the efficiency of a number of universal data compression algorithms. These bounds are non-asymptotic in the sense that they express the effect of limited training data on the compression efficiency.