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

Klass, Michael Jay and Nowicki, Krzysztof LU (2016) In Working Papers in Statistics
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.
Please use this url to cite or link to this publication:
author
and
organization
publishing date
type
Working paper/Preprint
publication status
published
subject
keywords
Unobserved species, estimation of population size, sequential estimation procedure, error probability
in
Working Papers in Statistics
issue
2016:1
pages
15 pages
publisher
Department of Statistics, Lund university
language
English
LU publication?
yes
id
d02dae25-6ec2-4d79-b21d-c8a44a0f935b
date added to LUP
2016-09-21 13:06:27
date last changed
2018-11-21 21:26:00
@misc{d02dae25-6ec2-4d79-b21d-c8a44a0f935b,
  abstract     = {{Let N be the number of classes in a population to be estimated. Fix any preassigned error probability 0&lt;epsilon&lt; 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.}},
  author       = {{Klass, Michael Jay and Nowicki, Krzysztof}},
  keywords     = {{Unobserved species; estimation of population size; sequential estimation procedure; error probability}},
  language     = {{eng}},
  note         = {{Working Paper}},
  number       = {{2016:1}},
  publisher    = {{Department of Statistics, Lund university}},
  series       = {{Working Papers in Statistics}},
  title        = {{Sequential Search Algorithm for Estimation of the Number of Classes in a Given Population}},
  url          = {{https://lup.lub.lu.se/search/files/12781616/15297_39417_1_PB.pdf}},
  year         = {{2016}},
}