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  • 1
    Online Resource
    Online Resource
    Cham : Springer International Publishing | Cham : Imprint: Springer
    UID:
    gbv_1741570611
    Format: 1 Online-Ressource(XII, 185 p. 60 illus., 13 illus. in color.)
    Edition: 1st ed. 2020.
    ISBN: 9783030607500
    Content: 1. Introduction -- 2. Probability Theory and Some Useful Probability Distribution -- 3. Choice of Prior Distribution -- 4. Elementary Bayesian Analyses -- 5. Hypothesis Testing and Model Choice -- 6. Linear Models -- 7. General Linear Models -- 8. Spatial Models.
    Content: This book presents modern Bayesian analysis in a format that is accessible to researchers in the fields of ecology, wildlife biology, and natural resource management. Bayesian analysis has undergone a remarkable transformation since the early 1990s. Widespread adoption of Markov chain Monte Carlo techniques has made the Bayesian paradigm the viable alternative to classical statistical procedures for scientific inference. The Bayesian approach has a number of desirable qualities, three chief ones being: i) the mathematical procedure is always the same, allowing the analyst to concentrate on the scientific aspects of the problem; ii) historical information is readily used, when appropriate; and iii) hierarchical models are readily accommodated. This monograph contains numerous worked examples and the requisite computer programs. The latter are easily modified to meet new situations. A primer on probability distributions is also included because these form the basis of Bayesian inference. Researchers and graduate students in Ecology and Natural Resource Management will find this book a valuable reference.
    Additional Edition: ISBN 9783030607494
    Additional Edition: ISBN 9783030607517
    Additional Edition: ISBN 9783030607524
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030607494
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030607517
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9783030607524
    Language: English
    URL: Cover
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