Semiparametric regression in capture-recapture modeling

Gimenez, Olivier and Crainiceanu, C. and Barbraud, C. and Jenouvrier, S. and Morgan, Byron J. T. (2006) Semiparametric regression in capture-recapture modeling. Biometrics, 62 (3). pp. 691-698. ISSN 0006-341X. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)

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Capture-recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in survival may be explained by incorporating relevant covariates. We propose nonparametric and semiparametric regression methods for estimating survival in capture-recapture models. A fully Bayesian approach using Markov chain Monte Carlo simulations was employed to estimate the model parameters. The work is illustrated by a study of Snow petrels, in which survival probabilities are expressed as nonlinear functions of a climate covariate, using data from a 40-year study on marked individuals, nesting at Petrels Island, Terre Adelie.

Item Type: Article
Uncontrolled keywords: auxiliary variables; Bayesian inference; demographic rates; environmental covariates; penalized splines; WinBUGS
Subjects: Q Science > QA Mathematics (inc Computing science)
Divisions: Faculties > Science Technology and Medical Studies > School of Mathematics Statistics and Actuarial Science > Statistics
Depositing User: Judith Broom
Date Deposited: 05 Sep 2008 20:14
Last Modified: 07 Jul 2014 13:03
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