Semiparametric regression in capture-recapture modeling

O. Gimenez, C. Crainiceanu, C. Barbraud, S. Jenouvrier, B. J.T. Morgan

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish (US)
Pages (from-to)691-698
Number of pages8
JournalBiometrics
Volume62
Issue number3
DOIs
StatePublished - Sep 2006

Keywords

  • Auxiliary variables
  • Bayesian inference
  • Demographic rates
  • Environmental covariates
  • Penalized splines
  • WinBUGS

ASJC Scopus subject areas

  • Statistics and Probability
  • Biochemistry, Genetics and Molecular Biology(all)
  • Immunology and Microbiology(all)
  • Agricultural and Biological Sciences(all)
  • Applied Mathematics

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  • Cite this

    Gimenez, O., Crainiceanu, C., Barbraud, C., Jenouvrier, S., & Morgan, B. J. T. (2006). Semiparametric regression in capture-recapture modeling. Biometrics, 62(3), 691-698. https://doi.org/10.1111/j.1541-0420.2005.00514.x