Semiparametric Regression in Capture-Recapture Modelling

• Main Authors: Gimenez, O., Barbraud, C., Crainiceanu, Ciprian M., Jenouvrier, S., Morgan, B.T.
• Format: Text
• Language: unknown
• Published: Collection of Biostatistics Research Archive 2004
• Subjects: Auxiliary variables; Bayesian inference; Demographic rates; Environmental covariates; Penalized splines; WinBUGS; Numerical Analysis and Computation; Statistical Methodology; Statistical Models; Statistical Theory; Snow Petrels
• Online Access: https://biostats.bepress.com/jhubiostat/paper66; https://biostats.bepress.com/cgi/viewcontent.cgi?article=1066&context=jhubiostat

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.