Bayesian inference with ecological applications
A mathematically sound but accessible and engaging introduction to the Bayesian paradigm, written specifically for ecologists and wildlife biologists.
Each example in this book could be taken as the mini project, coz it provides the BUG data and codes, mathematical descriptions behind the model and model comparisons in the example.
Some of the examples in this book are from the view point of Mark-Recapture framework as Richard J Barker is the expert in this area.
He's the Prof. of Statistics in the University of Otago, where I took my undergraduate studies.
PART I
PROBABILITY AND
INFERENCE
1. Introduction to Bayesian Inference 3
2. Probability 13
3. Statistical Inference 23
4. Calculating Posterior Distributions 47
PARTII
THE BAYESIAN
MAˉ RAMATANGA
5. Bayesian Prediction 77
6. Priors 109
7. Multimodel Inference 127
PARTIII
APPLICATIONS
8. Hidden Data Models 163
9. Closed-Population Mark-Recapture
Models 201
10. Latent Multinomial Models 225
11. Open Population Models 239
12. Individual Fitness 271
13. Autoregressive Smoothing 287
PARTIV
APPENDICES
A. Probability Rules 301
B. Probability Distributions 307