A simple variance formula for population size estimators by conditioning

Böhning, Dankmar (2008) A simple variance formula for population size estimators by conditioning Statistical Methodology, 5, (5), pp. 410-423. (doi:10.1016/j.stamet.2007.10.001).


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This note considers the variance estimation for population size estimators based on capture–recapture experiments. Whereas a diversity of estimators of the population size has been suggested, the question of estimating the associated variances is less frequently addressed. This note points out that the technique of conditioning can be applied here successfully which also allows us to identify sources of variation: the variance due to estimation of the model parameters and the binomial variance due to sampling nn units from a population of size NN. It is applied to estimators typically used in capture–recapture experiments in continuous time including the estimators of Zelterman and Chao and improves upon previously used variance estimators. In addition, knowledge of the variances associated with the estimators by Zelterman and Chao allows the suggestion of a new estimator as the weighted sum of the two. The decomposition of the variance into the two sources allows also a new understanding of how resampling techniques like the Bootstrap could be used appropriately. Finally, the sample size question for capture–recapture experiments is addressed. Since the variance of population size estimators increases with the sample size, it is suggested to use relative measures such as the observed-to-hidden ratio or the completeness of identification proportion for approaching the question of sample size choice.

Item Type: Article
Digital Object Identifier (DOI): doi:10.1016/j.stamet.2007.10.001
ISSNs: 1572-3127 (print)
Keywords: capture-recapture, population size, variance estimation, horvitz–thompson estimator
Organisations: Statistical Sciences Research Institute
ePrint ID: 210475
Date :
Date Event
September 2008Published
Date Deposited: 09 Feb 2012 13:31
Last Modified: 18 Apr 2017 00:27
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/210475

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