Estimating the size of an open population using sparse capture–recapture data

Estimating the size of an open population using sparse capture–recapture data IntroductionCapture–recapture data are commonly collected to estimate the size of a population. Amstrup et al. () and McCrea and Morgan () give recent overviews of the area. In the past, much of the focus has been on closed populations where there is no emigration, immigration, birth, or death. The comparative simplicity of this setting has allowed the development of diverse methods that weaken the traditional “urn model” assumptions (Otis et al., ). Open populations combine all the features of closed populations with the added complication that individuals can enter and leave the population. Thus, in most cases one does not know when a given individual first appeared in the population and when they departed. That is, the individuals available for capture on a given occasion cannot be specified as clearly as they can for a closed population where the population is fixed over the entire experiment. Here, we are motivated by and apply our methods to three capture–recapture data sets with regular capture occasions where the numbers of recaptures are generally low. The population corresponding to the first data set is large, to the second is small, and to the third is moderately large.Police reports of the daily contacts http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Biometrics Wiley

Estimating the size of an open population using sparse capture–recapture data

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Publisher
Wiley
Copyright
© 2018, The International Biometric Society
ISSN
0006-341X
eISSN
1541-0420
D.O.I.
10.1111/biom.12718
Publisher site
See Article on Publisher Site

Abstract

IntroductionCapture–recapture data are commonly collected to estimate the size of a population. Amstrup et al. () and McCrea and Morgan () give recent overviews of the area. In the past, much of the focus has been on closed populations where there is no emigration, immigration, birth, or death. The comparative simplicity of this setting has allowed the development of diverse methods that weaken the traditional “urn model” assumptions (Otis et al., ). Open populations combine all the features of closed populations with the added complication that individuals can enter and leave the population. Thus, in most cases one does not know when a given individual first appeared in the population and when they departed. That is, the individuals available for capture on a given occasion cannot be specified as clearly as they can for a closed population where the population is fixed over the entire experiment. Here, we are motivated by and apply our methods to three capture–recapture data sets with regular capture occasions where the numbers of recaptures are generally low. The population corresponding to the first data set is large, to the second is small, and to the third is moderately large.Police reports of the daily contacts

Journal

BiometricsWiley

Published: Jan 1, 2018

Keywords: ; ; ; ;

References

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