AStA Advances in Statistical Analysis

, Volume 93, Issue 1, pp 61–71

CAMCR: Computer-Assisted Mixture model analysis for Capture–Recapture count data

Original Paper

DOI: 10.1007/s10182-008-0092-z

Cite this article as:
Kuhnert, R. & Böhning, D. AStA Adv Stat Anal (2009) 93: 61. doi:10.1007/s10182-008-0092-z

Abstract

Population size estimation with discrete or nonparametric mixture models is considered, and reliable ways of construction of the nonparametric mixture model estimator are reviewed and set into perspective. Construction of the maximum likelihood estimator of the mixing distribution is done for any number of components up to the global nonparametric maximum likelihood bound using the EM algorithm. In addition, the estimators of Chao and Zelterman are considered with some generalisations of Zelterman’s estimator. All computations are done with CAMCR, a special software developed for population size estimation with mixture models. Several examples and data sets are discussed and the estimators illustrated. Problems using the mixture model-based estimators are highlighted.

Keywords

CAMCRCapture–recaptureChao’s and Zelterman’s estimator of population sizeMixture of truncated Poisson distributions

Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  1. 1.Division for Health of Children and Adolescents, Prevention ConceptsRobert Koch-InstituteBerlinGermany
  2. 2.Quantitative Biology and Applied StatisticsSchool of Biological SciencesReadingUK