Semiparametric Regression in Capture–Recapture Modeling
Article first published online: 1 FEB 2006
Volume 62, Issue 3, pages 691–698, September 2006
How to Cite
Gimenez, O., Crainiceanu, C., Barbraud, C., Jenouvrier, S. and Morgan, B. J. T. (2006), Semiparametric Regression in Capture–Recapture Modeling. Biometrics, 62: 691–698. doi: 10.1111/j.1541-0420.2005.00514.x
- Issue published online: 1 FEB 2006
- Article first published online: 1 FEB 2006
- Received December 2004. Revised October 2005. Accepted October 2005.
- Auxiliary variables;
- Bayesian inference;
- Demographic rates;
- Environmental covariates;
- Penalized splines;
Summary 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 Adélie.