Morgan / McCrea Analysis of Capture-Recapture Data

Erscheinungsjahr 2014
ISBN: 978-1-4398-3660-6
Verlag: Taylor & Francis
Format: PDF
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 314 Seiten

Reihe: Chapman & Hall/CRC Interdisciplinary Statistics

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.

Zielgruppe

Researchers and graduate students in statistics, biology, ecology, medicine, demography, and social sciences.

Autoren/Hrsg.

Morgan, Byron J. T.

McCrea, Rachel S.

Fachgebiete

• Naturwissenschaften Biowissenschaften Biowissenschaften Naturschutzbiologie, Biodiversität
• Interdisziplinäres Wissenschaften Wissenschaften: Forschung und Information Datenanalyse, Datenverarbeitung
• Geowissenschaften Umweltwissenschaften Biodiversität
• Naturwissenschaften Biowissenschaften Angewandte Biologie Biomathematik
• Sozialwissenschaften Soziologie | Soziale Arbeit Soziologie Allgemein Empirische Sozialforschung, Statistik

Inhaltsverzeichnis

Introduction
History and motivation
Marking
Introduction to the Cormorant data set
Modelling population dynamics

Model fitting, averaging, and comparison
Introduction
Classical inference
Bayesian inference
Computing

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

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

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

Occupancy modelling
Introduction
The two-parameter occupancy model
Extensions
Moving from species to individual: abundance-induced heterogeneity
Accounting for spatial information
Computing

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

Simultaneous estimation of survival and abundance
Introduction
Estimating abundance in open populations
Batch marking
Robust design
Stopover models
Computing

Goodness-of-fit assessment
Introduction
Diagnostic goodness-of-fit tests
Absolute goodness-of-fit tests
Computing

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

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

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.

Über Autor(innen)

Rachel S. McCrea is a NERC research fellow in the National Centre for Statistical Ecology at the University of Kent.

Byron J.T. Morgan is an Emeritus Professor and honorary professorial research fellow in the School of Mathematics, Statistics and Actuarial Science at the University of Kent. He is also the co-director of the National Centre for Statistical Ecology.