Estimation of population size in entropic perspective

Abstract

Nonparametric estimation of population size is a long standing and difficult problem. It is difficult because, particularly from a likelihood perspective, the underlying distribution could vary greatly and many small probability events may not be observed in a sample. However if approached from an entropic standpoint, certain trends can be exploited. This article proposes several estimators based on an entropic representation of population size, and establishes their consistency. Simulation results of the proposed estimators are also reported in comparison with a well-known estimator, and the advantages are noted. Two examples with real data are also included.