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Hierarchical modeling and inference in ecology : the analysis of data from populations, metapopulations and communities /

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the us...

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Bibliographic Details
Main Authors: Royle, J. Andrew
Corporate Authors: Elsevier Science & Technology
Group Author: Dorazio, Robert M
Published: Academic,
Publisher Address: Amsterdam ; Boston :
Publication Dates: 2008.
Literature type: eBook
Language: English
Edition: First edition.
Subjects:
Spatial ecology > Mathematical models
Spatial ecology > Computer simulation
SCIENCE > Environmental Science see also Chemistry > Environmental
NATURE > Ecosystems & Habitats > Wilderness
NATURE > Ecology
SCIENCE > Life Sciences > Ecology
Electronic books
Online Access: http://www.sciencedirect.com/science/book/9780123740977
Summary: A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The
Carrier Form: 1 online resource (xviii, 444 pages, [8] pages of plates) : illustrations (some color), maps (some color)
Bibliography: Includes bibliographical references (pages 417-437) and index.
ISBN: 9780123740977
0123740975
9780080559254
0080559255
Index Number: QH541
CLC: Q141
Contents: Introduction; Site-occupancy models; Closed population models; Modelling individual effects in closed populations; Abundance as a state variable; Abundance as a state variable; Dynamic site occupancy models; Cormack-Jolly-Seber models; Jolly-Seber models; Animal community models; Occupancy models with spatial dynamics; Open models for animal communities; Temporaly dynamic models for abundance; Other potential topics; Statistical concepts and philosophy; Appendices (online or in text) -- Appendix1: R-tutorial, Sample R-functions for implementing several methods -- Appendix2: WinBUGS tutorial

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