Open Access
May 2016 Trace-Contrast Models for Capture–Recapture Without Capture Histories
R. M. Fewster, B. C. Stevenson, D. L. Borchers
Statist. Sci. 31(2): 245-258 (May 2016). DOI: 10.1214/16-STS551


Capture–recapture studies increasingly rely upon natural tags that allow animals to be identified by features such as coat markings, DNA profiles, acoustic profiles, or spatial locations. These innovations greatly increase the number of capture samples achievable and enable capture–recapture estimation for many inaccessible and elusive species. However, natural features are invariably imperfect as indicators of identity. Drawing on the recently developed Palm likelihood approach to parameter estimation in clustered point processes, we propose a new estimation framework based on comparing pairs of detections, which we term the trace-contrast framework. Importantly, no reconstruction of capture histories is needed. We show that we can achieve accurate, precise, and computationally fast inference. We illustrate the methods with a camera-trap study of a partially marked population of ship rats (Rattus rattus) in New Zealand.


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R. M. Fewster. B. C. Stevenson. D. L. Borchers. "Trace-Contrast Models for Capture–Recapture Without Capture Histories." Statist. Sci. 31 (2) 245 - 258, May 2016.


Published: May 2016
First available in Project Euclid: 24 May 2016

zbMATH: 06946225
MathSciNet: MR3506103
Digital Object Identifier: 10.1214/16-STS551

Keywords: Camera-traps , mark recapture , natural tags , Neyman–Scott process , palm likelihood estimation , Rattus species

Rights: Copyright © 2016 Institute of Mathematical Statistics

Vol.31 • No. 2 • May 2016
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