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

Includes bibliographical references and index.

1 PREVIEW;
2 DETERMINISTIC MODELS;
3 PRINCIPLES OF PROBABILITY;
4 LIKELIHOOD;
5 SIMPLE BAYESIAN MODELS;
6 HIERARCHICAL BAYESIAN MODELS;
7 MARKOV CHAIN MONTE CARLO;
8 INFERENCE FROM A SINGLE MODEL;
9 INFERENCE FROM MULTIPLE MODELS;
10 WRITING BAYESIAN MODELS;
11 PROBLEMS;
12 SOLUTIONS.

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.