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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

Record Type:	Electronic resources : Monograph/item
Title/Author:	Introduction to Bayesian methods in ecology and natural resources/ by Edwin J. Green, Andrew O. Finley, William E. Strawderman.
Author:	Green, Edwin J.
other author:	Finley, Andrew O.
Published:	Cham :Springer International Publishing : : 2020.,
Description:	xii, 185 p. :ill., digital ;24 cm.
[NT 15003449]:	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
Subject:	Applied ecology - Statistical methods. -
Online resource:	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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100 1 $a Green, Edwin J. $3 3527404
245 1 0 $a Introduction to Bayesian methods in ecology and natural resources $h [electronic resource] / $c by Edwin J. Green, Andrew O. Finley, William E. Strawderman.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2020.
300 $a xii, 185 p. : $b ill., digital ; $c 24 cm.
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.
650 0 $a Applied ecology $x Statistical methods. $3 3527407
650 0 $a Bayesian statistical decision theory. $3 551404
650 1 4 $a Applied Ecology. $3 890960
650 2 4 $a Statistics for Life Sciences, Medicine, Health Sciences. $3 891086
650 2 4 $a Animal Ecology. $3 895065
650 2 4 $a Forestry Management. $3 895131
700 1 $a Finley, Andrew O. $3 3527405
700 1 $a Strawderman, William E. $3 3527406
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-60750-0
950 $a Biomedical and Life Sciences (SpringerNature-11642)