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The Resource Bayesian models : a statistical primer for ecologists, N. Thompson Hobbs and Mevin B. Hooten

Bayesian models : a statistical primer for ecologists, N. Thompson Hobbs and Mevin B. Hooten

Label
Bayesian models : a statistical primer for ecologists
Title
Bayesian models
Title remainder
a statistical primer for ecologists
Statement of responsibility
N. Thompson Hobbs and Mevin B. Hooten
Creator
Contributor
Author
Subject
Language
eng
Summary
Bayesian modeling has become an indispensable tool for ecological research because it is uniquely suited to deal with complexity in a statistically coherent way. This textbook provides a comprehensive and accessible introduction to the latest Bayesian methods-in language ecologists can understand. Unlike other books on the subject, this one emphasizes the principles behind the computations, giving ecologists a big-picture understanding of how to implement this powerful statistical approach. Bayesian Models is an essential primer for non-statisticians. It begins with a definition of probabili
Cataloging source
AU@
Index
index present
Language note
In English
Literary form
non fiction
Nature of contents
  • dictionaries
  • bibliography
Bayesian models : a statistical primer for ecologists, N. Thompson Hobbs and Mevin B. Hooten
Label
Bayesian models : a statistical primer for ecologists, N. Thompson Hobbs and Mevin B. Hooten
Link
http://www.jstor.org/stable/10.2307/j.ctt1dr36kz
Publication
Copyright
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Bibliography note
Includes bibliographical references and index
Carrier category
online resource
Carrier category code
cr
Carrier MARC source
rdacarrier
Content category
text
Content type code
txt
Content type MARC source
rdacontent
Contents
  • Cover; Title; Copyright; Contents; Preface; I Fundamentals; 1 PREVIEW; 1.1 A Line of Inference for Ecology; 1.2 An Example Hierarchical Model; 1.3 What Lies Ahead?; 2 DETERMINISTIC MODELS; 2.1 Modeling Styles in Ecology; 2.2 A Few Good Functions; 3 PRINCIPLES OF PROBABILITY; 3.1 Why Bother with First Principles?; 3.2 Rules of Probability; 3.3 Factoring Joint Probabilities; 3.4 Probability Distributions; 4 LIKELIHOOD; 4.1 Likelihood Functions; 4.2 Likelihood Profiles; 4.3 Maximum Likelihood; 4.4 The Use of Prior Information in Maximum Likelihood; 5 SIMPLE BAYESIAN MODELS; 5.1 Bayes' Theorem
  • 5.2 The Relationship between Likelihood and Bayes'5.3 Finding the Posterior Distribution in Closed Form; 5.4 More about Prior Distributions; 6 HIERARCHICAL BAYESIAN MODELS; 6.1 What Is a Hierarchical Model?; 6.2 Example Hierarchical Models; 6.3 When Are Observation and Process Variance Identifiable?; II Implementation; 7 MARKOV CHAIN MONTE CARLO; 7.1 Overview; 7.2 How Does MCMC Work?; 7.3 Specifics of the MCMC Algorithm; 7.4 MCMC in Practice; 8 INFERENCE FROM A SINGLE MODEL; 8.1 Model Checking; 8.2 Marginal Posterior Distributions; 8.3 Derived Quantities
  • 8.4 Predictions of Unobserved Quantities8.5 Return to the Wildebeest; 9 INFERENCE FROM MULTIPLE MODELS; 9.1 Model Selection; 9.2 Model Probabilities and Model Averaging; 9.3 Which Method to Use?; III Practice in Model Building; 10 WRITING BAYESIAN MODELS; 10.1 A General Approach; 10.2 An Example of Model Building: Aboveground Net Primary Production in Sagebrush Steppe; 11 PROBLEMS; 11.1 Fisher's Ticks; 11.2 Light Limitation of Trees; 11.3 Landscape Occupancy of Swiss Breeding Birds; 11.4 Allometry of Savanna Trees; 11.5 Movement of Seals in the North Atlantic; 12 SOLUTIONS
  • 12.1 Fisher's Ticks12.2 Light Limitation of Trees; 12.3 Landscape Occupancy of Swiss Breeding Birds; 12.4 Allometry of Savanna Trees; 12.5 Movement of Seals in the North Atlantic; Afterword; Acknowledgments; A Probability Distributions and Conjugate Priors; Bibliography; Index
http://library.link/vocab/cover_art
https://contentcafe2.btol.com/ContentCafe/Jacket.aspx?Return=1&Type=S&Value=9781400866557&userID=ebsco-test&password=ebsco-test
Dimensions
unknown
http://library.link/vocab/discovery_link
{'f': 'http://opac.lib.rpi.edu/record=b4400886'}
Extent
1 online resource (xiv, 300 pages)
Form of item
online
Isbn
9781400866557
Media category
computer
Media MARC source
rdamedia
Media type code
c
Specific material designation
remote

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