Topic
WinBUGS
Bayesian inference
9
Auxiliary variables
8
Demographic rates
8
[MATH]Mathematics [math]
8
environmental covariates
8
[SDE]Environmental Sciences
7
penalized splines
7
Penalized splines
2
Anesthesiology and Pain Medicine
1
Cardiology
1
Cardiology and Cardiovascular Medicine
1
Cardiovascular Disease
1
Census data
1
Environmental covariates
1
Human
1
Integrated analysis
1
Kalman filter
1
Logistic regression
1
Meta-Analysis as Topic
1
Numerical Analysis and Computation
1
QL1-991
1
Ring-recovery data
1
Specialization
1
State-space model
1
Statistical Methodology
1
Statistical Models
1
Statistical Theory
1
Zoology
1
auxiliary variables
1
demographic rates
1
evidence
1
head-to-head meta-analysi
1
network meta-analysi
1
one frequently encounters both count and mark-recapture-recovery data. Here
1
we consider an integrated Bayesian analysis of ring¿recovery and count data using a state-space model. We then impose a Leslie-matrix-based model on the true population counts describing the natural birth-death and age transition processes. We focus upon the analysis of both count and recovery data collected on British lapwings (Vanellus vanellus) combined with records of the number of frost days each winter. We demonstrate how the combined analysis of these data provides a more robust inferential framework and discuss how the Bayesian approach using MCMC allows us to remove the potentially restrictive normality assumptions commonly assumed for analyses of this sort. It is shown how WinBUGS may be used to perform the Bayesian analysis. WinBUGS code is provided and its performance is critically discussed
1