Introduction To Bayesian Methods In Ecology And Natural Resources

Author : Edwin J. Green
Publisher : Springer Nature
ISBN 13 : 303060750X
Total Pages : 188 pages
Book Rating : 4.00/5 ( download)

DOWNLOAD NOW!

Download or read book Introduction to Bayesian Methods in Ecology and Natural Resources written by Edwin J. Green and published by Springer Nature. This book was released on 2020-11-26 with total page 188 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Author : N. Thompson Hobbs
Publisher : Princeton University Press
ISBN 13 : 1400866553
Total Pages : 315 pages
Book Rating : 4.57/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Models written by N. Thompson Hobbs and published by Princeton University Press. This book was released on 2015-08-04 with total page 315 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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 probability and develops a step-by-step sequence of connected ideas, including basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding, favoring instead a concise presentation of the mathematical statistics needed to understand how and why Bayesian analysis works. It also explains how to write out properly formulated hierarchical Bayesian models and use them in computing, research papers, and proposals. This primer enables ecologists to understand the statistical principles behind Bayesian modeling and apply them to research, teaching, policy, and management. Presents the mathematical and statistical foundations of Bayesian modeling in language accessible to non-statisticians Covers basic distribution theory, network diagrams, hierarchical models, Markov chain Monte Carlo, and more Deemphasizes computer coding in favor of basic principles Explains how to write out properly factored statistical expressions representing Bayesian models

Author : Eric Parent
Publisher : CRC Press
ISBN 13 : 1584889209
Total Pages : 427 pages
Book Rating : 4.05/5 ( download)

DOWNLOAD NOW!

Download or read book Introduction to Hierarchical Bayesian Modeling for Ecological Data written by Eric Parent and published by CRC Press. This book was released on 2012-08-21 with total page 427 pages. Available in PDF, EPUB and Kindle. Book excerpt: Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian Modeling for Ecological Data gives readers a flexible and effective framework to learn about complex ecological processes from various sources of data. It also helps readers get started on building their own statisti

Author : William A Link
Publisher : Academic Press
ISBN 13 : 0080889808
Total Pages : 354 pages
Book Rating : 4.01/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Inference written by William A Link and published by Academic Press. This book was released on 2009-08-07 with total page 354 pages. Available in PDF, EPUB and Kindle. Book excerpt: This text is written to provide a mathematically sound but accessible and engaging introduction to Bayesian inference specifically for environmental scientists, ecologists and wildlife biologists. It emphasizes the power and usefulness of Bayesian methods in an ecological context. The advent of fast personal computers and easily available software has simplified the use of Bayesian and hierarchical models . One obstacle remains for ecologists and wildlife biologists, namely the near absence of Bayesian texts written specifically for them. The book includes many relevant examples, is supported by software and examples on a companion website and will become an essential grounding in this approach for students and research ecologists. Engagingly written text specifically designed to demystify a complex subject Examples drawn from ecology and wildlife research An essential grounding for graduate and research ecologists in the increasingly prevalent Bayesian approach to inference Companion website with analytical software and examples Leading authors with world-class reputations in ecology and biostatistics

Author : Ruth King
Publisher : CRC Press
ISBN 13 : 1439811881
Total Pages : 457 pages
Book Rating : 4.87/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Analysis for Population Ecology written by Ruth King and published by CRC Press. This book was released on 2009-10-30 with total page 457 pages. Available in PDF, EPUB and Kindle. Book excerpt: Emphasizing model choice and model averaging, this book presents up-to-date Bayesian methods for analyzing complex ecological data. It provides a basic introduction to Bayesian methods that assumes no prior knowledge. The book includes detailed descriptions of methods that deal with covariate data and covers techniques at the forefront of research, such as model discrimination and model averaging. Leaders in the statistical ecology field, the authors apply the theory to a wide range of actual case studies and illustrate the methods using WinBUGS and R. The computer programs and full details of the data sets are available on the book's website.

Author : Michael A. McCarthy
Publisher : Cambridge University Press
ISBN 13 : 113946387X
Total Pages : 310 pages
Book Rating : 4.74/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Methods for Ecology written by Michael A. McCarthy and published by Cambridge University Press. This book was released on 2007-05-10 with total page 310 pages. Available in PDF, EPUB and Kindle. Book excerpt: The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required analyses. McCarthy bridges that gap, using a clear and accessible style. The text also incorporates case studies to demonstrate mark-recapture analysis, development of population models and the use of subjective judgement. The advantages of Bayesian methods, are also described here, for example, the incorporation of any relevant prior information and the ability to assess the evidence in favour of competing hypotheses. Free software is available as well as an accompanying web-site containing the data files and WinBUGS codes. Bayesian Methods for Ecology will appeal to academic researchers, upper undergraduate and graduate students of Ecology.

Author : Howard B. Stauffer
Publisher : John Wiley & Sons
ISBN 13 : 0470185074
Total Pages : 418 pages
Book Rating : 4.70/5 ( download)

DOWNLOAD NOW!

Download or read book Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists written by Howard B. Stauffer and published by John Wiley & Sons. This book was released on 2007-12-14 with total page 418 pages. Available in PDF, EPUB and Kindle. Book excerpt: The first all-inclusive introduction to modern statistical research methods in the natural resource sciences The use of Bayesian statistical analysis has become increasingly important to natural resource scientists as a practical tool for solving various research problems. However, many important contemporary methods of applied statistics, such as generalized linear modeling, mixed-effects modeling, and Bayesian statistical analysis and inference, remain relatively unknown among researchers and practitioners in this field. Through its inclusive, hands-on treatment of real-world examples, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists successfully introduces the key concepts of statistical analysis and inference with an accessible, easy-to-follow approach. The book provides case studies illustrating common problems that exist in the natural resource sciences and presents the statistical knowledge and tools needed for a modern treatment of these issues. Subsequent chapter coverage features: An introduction to the fundamental concepts of Bayesian statistical analysis, including its historical background, conjugate solutions, Bayesian hypothesis testing and decision-making, and Markov Chain Monte Carlo solutions The relevant advantages of using Bayesian statistical analysis, rather than the traditional frequentist approach, to address research problems Two alternative strategies—the a posteriori model selection strategy and the a priori parsimonious model selection strategy using AIC and DIC—to model selection and inference The ideas of generalized linear modeling (GLM), focusing on the most popular GLM of logistic regression An introduction to mixed-effects modeling in S-Plus® and R for analyzing natural resource data sets with varying error structures and dependencies Each statistical concept is accompanied by an illustration of its frequentist application in S-Plus® or R as well as its Bayesian application in WinBUGS. Brief introductions to these software packages are also provided to help the reader fully understand the concepts of the statistical methods that are presented throughout the book. Assuming only a minimal background in introductory statistics, Contemporary Bayesian and Frequentist Statistical Research Methods for Natural Resource Scientists is an ideal text for natural resource students studying statistical research methods at the upper-undergraduate or graduate level and also serves as a valuable problem-solving guide for natural resource scientists across a broad range of disciplines, including biology, wildlife management, forestry management, fisheries management, and the environmental sciences.

Author : Michael A. McCarthy
Publisher :
ISBN 13 : 9780511284946
Total Pages : 312 pages
Book Rating : 4.42/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Methods for Ecology written by Michael A. McCarthy and published by . This book was released on 2007 with total page 312 pages. Available in PDF, EPUB and Kindle. Book excerpt: An accessible text describing how to use Bayesian methods of statistical analysis in ecology.

Author : Franzi Korner-Nievergelt
Publisher : Academic Press
ISBN 13 : 0128016787
Total Pages : 329 pages
Book Rating : 4.87/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan written by Franzi Korner-Nievergelt and published by Academic Press. This book was released on 2015-04-04 with total page 329 pages. Available in PDF, EPUB and Kindle. Book excerpt: Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods of conducting data analyses. The book provides the theoretical background in an easy-to-understand approach, encouraging readers to examine the processes that generated their data. Including discussions of model selection, model checking, and multi-model inference, the book also uses effect plots that allow a natural interpretation of data. Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN introduces Bayesian software, using R for the simple modes, and flexible Bayesian software (BUGS and Stan) for the more complicated ones. Guiding the ready from easy toward more complex (real) data analyses ina step-by-step manner, the book presents problems and solutions—including all R codes—that are most often applicable to other data and questions, making it an invaluable resource for analyzing a variety of data types. Introduces Bayesian data analysis, allowing users to obtain uncertainty measurements easily for any derived parameter of interest Written in a step-by-step approach that allows for eased understanding by non-statisticians Includes a companion website containing R-code to help users conduct Bayesian data analyses on their own data All example data as well as additional functions are provided in the R-package blmeco

Author : Therese M. Donovan
Publisher : Oxford University Press, USA
ISBN 13 : 0198841299
Total Pages : 430 pages
Book Rating : 4.96/5 ( download)

DOWNLOAD NOW!

Download or read book Bayesian Statistics for Beginners written by Therese M. Donovan and published by Oxford University Press, USA. This book was released on 2019 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: This is an entry-level book on Bayesian statistics written in a casual, and conversational tone. The authors walk a reader through many sample problems step-by-step to provide those with little background in math or statistics with the vocabulary, notation, and understanding of the calculations used in many Bayesian problems.