Analysis of capture-recapture data
Material type:
- 9781439836590
- 519.5 M2A6
Item type | Current library | Item location | Collection | Shelving location | Call number | Status | Date due | Barcode | |
---|---|---|---|---|---|---|---|---|---|
Books | Vikram Sarabhai Library | Rack 28-B / Slot 1414 (0 Floor, East Wing) | Non-fiction | General Stacks | 519.5 M2A6 (Browse shelf(Opens below)) | Available | 190979 |
Table of Contents:
1. Introduction
• History and motivation
• Marking
• Introduction to the Cormorant data set
• Modelling population dynamics
2. Model fitting, averaging, and comparison
• Introduction
• Classical inference
• Bayesian inference
• Computing
3. Estimating the size of closed populations
• Introduction
• The Schnabel census
• Analysis of Schnabel census data
• Model classes
• Accounting for unobserved heterogeneity
• Logistic-linear models
• Spuriously large estimates, penalized likelihood and elicited priors
• Bayesian modeling
• Medical and social applications
• Testing for closure-mixture estimators
• Spatial capture-recapture models
• Computing
4. Survival modeling: single-site models
• Introduction
• Mark-recovery models
• Mark-recapture models
• Combining separate mark-recapture and recovery data sets
• Joint recapture-recovery models
• Computing
5. Survival modeling: multi-site models
• Introduction
• Matrix representation
• Multi-site joint recapture-recovery models
• Multi-state models as a unified framework
• Extensions to multi-state models
• Model selection for multi-site models
• Multi-event models
• Computing
6. Occupancy modeling
• Introduction
• The two-parameter occupancy model
• Extensions
• Moving from species to individual: abundance-induced heterogeneity
• Accounting for spatial information
• Computing
7. Covariates and random effects
• Introduction
• External covariates
• Threshold models
• Individual covariates
• Random effects
• Measurement error
• Use of P-splines
• Senescence
• Variable selection
• Spatial covariates
• Computing
8. Simultaneous estimation of survival and abundance
• Introduction
• Estimating abundance in open populations
• Batch marking
• Robust design
• Stopover models
• Computing
9. Goodness-of-fit assessment
• Introduction
• Diagnostic goodness-of-fit tests
• Absolute goodness-of-fit tests
• Computing
10. Parameter redundancy
• Introduction
• Using symbolic computation
• Parameter redundancy and identifiability
• Decomposing the derivative matrix of full rank models
• Extension
• The moderating effect of data
• Covariates
• Exhaustive summaries and model taxonomies
• Bayesian methods
• Computing
11. State-space models
• Introduction
• Definitions
• Fitting linear Gaussian models
• Models which are not linear Gaussian
• Bayesian methods for state-space models
• Formulation of capture-re-encounter models
• Formulation of occupancy models
• Computing
12. Integrated population modeling
• Introduction
• Normal approximations of component likelihoods
• Model selection
• Goodness of fit for integrated population modelling: calibrated simulation
• Previous applications
• Hierarchical modelling to allow for dependence of data sets
• Computing
Appendix: Distributions reference
Summary, Further reading, and Exercises appear at the end of each chapter.
An important first step in studying the demography of wild animals is to identify the animals uniquely through applying markings, such as rings, tags, and bands. Once the animals are encountered again, researchers can study different forms of capture-recapture data to estimate features, such as the mortality and size of the populations. Capture-recapture methods are also used in other areas, including epidemiology and sociology.
With an emphasis on ecology, Analysis of Capture-Recapture Data covers many modern developments of capture-recapture and related models and methods and places them in the historical context of research from the past 100 years. The book presents both classical and Bayesian methods.
A range of real data sets motivates and illustrates the material and many examples illustrate biometry and applied statistics at work. In particular, the authors demonstrate several of the modeling approaches using one substantial data set from a population of great cormorants. The book also discusses which computer programs to use for implementing the models and contains 130 exercises that extend the main material. The data sets, computer programs, and other ancillaries are available at www.capturerecapture.co.uk.
The book is accessible to advanced undergraduate and higher-level students, quantitative ecologists, and statisticians. It helps readers understand model formulation and applications, including the technicalities of model diagnostics and checking.
(https://www.crcpress.com/Analysis-of-Capture-Recapture-Data/McCrea-Morgan/9781439836590)
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