Bayesian Models
A Statistical Primer for Ecologists, 2nd Edition
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Estimated delivery time: In stock at the publisher, but not at Prospero's office. Delivery time approx. 3-5 weeks.
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Product details:
- Publisher Princeton University Press
- Date of Publication 12 August 2025
- Number of Volumes Print PDF
- ISBN 9780691250120
- Binding Hardback
- No. of pages360 pages
- Size 234x155 mm
- Language English
- Illustrations 53 b/w illus. 6 tables. 755
Categories
Long description:
A fully updated and expanded edition of the essential primer on Bayesian modeling for ecologists
Uniquely suited to deal with complexity in a statistically coherent way, Bayesian modeling has become an indispensable tool for ecological research. This book teaches the basic principles of mathematics and statistics needed to apply Bayesian models to the analysis of ecological data, using language non-statisticians can understand. Deemphasizing computer coding in favor of a clear treatment of model building, it starts with a definition of probability and proceeds step-by-step through distribution theory, likelihood, simple Bayesian models, and hierarchical Bayesian models. Now revised and expanded, Bayesian Models enables students and practitioners to gain new insights from ecological models and data properly tempered by uncertainty.
- Covers the basic rules of probability needed to model diverse types of ecological data in the Bayesian framework
- Shows how to write proper mathematical expressions for posterior distributions using directed acyclic graphs as templates
- Explains how to use the powerful Markov chain Monte Carlo algorithm to find posterior distributions of model parameters, latent states, and missing data
- Teaches how to check models to assure they meet the assumptions of model-based inference
- Demonstrates how to make inferences from single and multiple Bayesian models
- Provides worked problems for practicing and strengthening modeling skills
- Features new chapters on spatial models and modeling missing data
