Semiparametric Regression in Capture-Recapture Modelling

O. Gimenez, Institute of Mathematics, Statistics & Actuarial Science, University of Kent, United Kingdom & Centre d'Ecologie Fonctionnelle et Evolutive-CNRS, France
C. Barbraud, Centre d'Etudes Biologiques de Chize, France
Ciprian M. Crainiceanu, Johns Hokins Bloomberg School of Public Health, Department of Biostatistics
S. Jenouvrier, Centre d'Etudes Biologiques de Chize, France
B.T. Morgan, Institute of Mathematics, Statistics & Actuarial Science, University of Kent, United Kingdom

Abstract

Capture-recapture models were developed to estimate survival using data arising from marking and monitoring wild animals over time. Variation in the survival process may be explained by incorporating relevant covariates. We develop nonparametric and semiparametric regression models for estimating survival in capture-recapture models. A fully Bayesian approach using MCMC 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.