Error analysis of entropy estimator for a memory-less information source

Summary form only given. The paper presents analytical formulations of the most important estimation errors, i.e., averaged squared bias error and mean squared error, for the class of entropy estimator expressed as a sum of arbitrary single variable functions. The class of entropy estimators includes all important entropy estimators that have been proposed heretofore. The important conventional entropy estimators are compared from the view point of the relation of those estimation errors.