Sequential Search Algorithm for Estimation of the Number of Classes in a Given Population

Authors

  • Michael Jay Klass Department of Statistics and Mathematics University of California, Berkeley Berkeley, CA 94720-3860
  • Krzysztof Nowicki Department of Statistics School of Economics and Management Lund University Box 743, SE-22007 Lund, Sweden

Keywords:

Unobserved species, estimation of population size, sequential estimation procedure, error probability

Abstract

Let N be the number of classes in a population to be estimated. Fix any preassigned error probability

0<epsilon< exp(-2) (roughly). We present a sequential search algorithm to estimate the exact value of N, with an error probability of at most epsilon, regardless of the value of N.

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Published

2016-01-07

Issue

2016

Section

Working Papers in Statistics