Statistical Science

Trace-Contrast Models for Capture–Recapture Without Capture Histories

R. M. Fewster, B. C. Stevenson, and D. L. Borchers

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Abstract

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.

Article information

Source
Statist. Sci., Volume 31, Number 2 (2016), 245-258.

Dates
First available in Project Euclid: 24 May 2016

Permanent link to this document
https://projecteuclid.org/euclid.ss/1464105041

Digital Object Identifier
doi:10.1214/16-STS551

Mathematical Reviews number (MathSciNet)
MR3506103

Zentralblatt MATH identifier
06946225

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

Citation

Fewster, R. M.; Stevenson, B. C.; Borchers, D. L. Trace-Contrast Models for Capture–Recapture Without Capture Histories. Statist. Sci. 31 (2016), no. 2, 245--258. doi:10.1214/16-STS551. https://projecteuclid.org/euclid.ss/1464105041


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