Title Introduction to hierarchical Bayesian modeling for ecological data / Éric Parent, Étienne Rivot

Published Boca Raton, FL : Taylor & Francis, [2013] ©2013

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Description 1 online resource (xxi, 402 pages) : illustrations Series Chapman & Hall/CRC applied environmental statistics Applied environmental statistics. Contents 1. Basic blocks of Bayesian modeling -- 2. More elaborate hierarchical structures Summary Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the author Notes "A CRC title." Bibliography Includes bibliographical references (pages 375-402) and index Notes Online resource; title from PDF title page (Taylor & Francis, March 17, 2023) Subject Ecology -- Statistical methods Bayesian statistical decision theory. Ecology. Ecology Bayes Theorem ecology. NATURE -- Ecology. NATURE -- Ecosystems & Habitats -- Wilderness. SCIENCE -- Environmental Science. SCIENCE -- Life Sciences -- Ecology. Ecology Bayesian statistical decision theory Ecology -- Statistical methods Form Electronic book Author Rivot, Etienne, 1974- author. ISBN 9781584889205 1584889209 9781299992382 1299992382

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