Population size estimation based upon zero-truncated, one-inflated and sparse count data

Dankmar Böhning () and Herwig Friedl ()
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Dankmar Böhning: University of Southampton
Herwig Friedl: Graz University of Technology

Statistical Methods & Applications, 2021, vol. 30, issue 4, No 5, 1197-1217

Abstract: Abstract Estimating the size of a hard-to-count population is a challenging matter. In particular, when only few observations of the population to be estimated are available. The matter gets even more complex when one-inflation occurs. This situation is illustrated with the help of two examples: the size of a dice snake population in Graz (Austria) and the number of flare stars in the Pleiades. The paper discusses how one-inflation can be easily handled in likelihood approaches and also discusses how variances and confidence intervals can be obtained by means of a semi-parametric bootstrap. A Bayesian approach is mentioned as well and all approaches result in similar estimates of the hidden size of the population. Finally, a simulation study is provided which shows that the unconditional likelihood approach as well as the Bayesian approach using Jeffreys’ prior perform favorable.

Keywords: Capture–recapture; Zero-truncation; One-inflation (search for similar items in EconPapers)
Date: 2021
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DOI: 10.1007/s10260-021-00556-8

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