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Introduction to Bayesian methods in ...

Green, Edwin J.

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Introduction to Bayesian methods in ecology and natural resources

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	Introduction to Bayesian methods in ecology and natural resources/ by Edwin J. Green, Andrew O. Finley, William E. Strawderman.
作者:	Green, Edwin J.
其他作者:	Finley, Andrew O.
出版者:	Cham :Springer International Publishing : : 2020.,
面頁冊數:	xii, 185 p. :ill., digital ;24 cm.
內容註:	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.
Contained By:	Springer Nature eBook
標題:	Applied ecology - Statistical methods. -
電子資源:	https://doi.org/10.1007/978-3-030-60750-0
ISBN:	9783030607500

Introduction to Bayesian methods in ecology and natural resources
Green, Edwin J.

Introduction to Bayesian methods in ecology and natural resources[electronic resource] /by Edwin J. Green, Andrew O. Finley, William E. Strawderman. - Cham :Springer International Publishing :2020. - xii, 185 p. :ill., digital ;24 cm.

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.

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.

ISBN: 9783030607500

Standard No.: 10.1007/978-3-030-60750-0doiSubjects--Topical Terms:

3527407
Applied ecology
--Statistical methods.

LC Class. No.: QH541.29 / .G74 2020

Dewey Class. No.: 577.01519

Introduction to Bayesian methods in ecology and natural resources
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505 0 $a 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.
520 $a 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.
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