Simple entropy estimator for small datasets

A pragmatic approach for entropy estimation is presented. It is based on coincidence detection and its application leads to a simple algorithm with two attractive features: the method can be used without any a priori knowledge concerning the source alphabet cardinality (K) and it can provide useful, though biased, estimates even when the number of samples is less than K.