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

Michael Jay Klass, Krzysztof Nowicki

Research output: Working paper/PreprintWorking paper

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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.
Original languageEnglish
PublisherDepartment of Statistics, Lund university
Number of pages15
Publication statusPublished - 2016

Publication series

NameWorking Papers in Statistics
PublisherDepartment of Statistics, Lund University
No.2016:1

Subject classification (UKÄ)

  • Probability Theory and Statistics

Free keywords

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

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