Estimating survival and transition rates from aggregate sightings of animals

Viallefont, A. and Besbeas, P.T. and Morgan, B.J.T. and McCrea, R.S. (2012) Estimating survival and transition rates from aggregate sightings of animals. Journal of Ornithology, 152 (s2). pp. 381-391. ISSN 0021-8375. (The full text of this publication is not available from this repository)

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Official URL
http://dx.doi.org/10.1007/s10336-010-0588-7

Abstract

We compare and contrast two methods for fitting probability models to data which arise when animals are marked in batches, without individual identification, and live in several different sites or states. The methods are suitable for populations in which animals are marked at birth and then resighted over several sites/states, for small animals going through several growth stages (insects, amphibiae, etc.), as well as for the follow-up of animals released after laboratory colour-marking, for example. The methods we consider include a multi-state model for resightings of batch-marked animals, allowing us to estimate survival, transitions, and sighting probabilities. One method is based on the EM algorithm, and the second uses the Kalman filter for computing likelihoods. The methods are illustrated on real data from a cohort of Great Cormorants Phalacrocorax carbo, and their performance is evaluated using simulation. We recommend identifying the batches, for instance in the case of sites, by using a different colour on each site at the time of marking, and in general the use of the Kalman filter rather than the EM-based approach.

Item Type: Article
Uncontrolled keywords: Aggregate survival data – Batch-marking – Grouped data – Interval censoring – Macrodata
Subjects: Q Science > QA Mathematics (inc Computing science) > QA276 Mathematical statistics
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Rachel McCrea
Date Deposited: 13 Jun 2012 11:35
Last Modified: 16 Oct 2012 09:13
Resource URI: http://kar.kent.ac.uk/id/eprint/29647 (The current URI for this page, for reference purposes)
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