Introduction to hierarchical Bayesian modeling for ecological data
2013
Parent, E. (Eric) | Rivot, Etienne
French environmental scientists Parent (National School of Rural Water and Forestry Engineering, Paris) and Rivot (Institute for Agronomic Research) walk colleagues through the first steps of statistical modeling and inference, particularly hierarchical Bayesian modeling, which they characterize as a golden key that allows ecologists to free their creativity and designs statistical models of their own. Moving from simple to more complex, they consider such aspects as the beta-binomial model, the basic normal model, combining various sources of information, nonlinear models for analyzing stock recruitment, piling up simple layers, and decision and planning. Annotation ©2012 Book News, Inc., Portland, OR (booknews.com).
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