Bayesian Methods For Ecology

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Bayesian Methods for Ecology

Michael A. McCarthy
Bayesian Methods for Ecology Book PDF

Author : Michael A. McCarthy
Publisher : Cambridge University Press
Page : 310 pages
File Size : 55,7 Mb
Release : 2007-05-10
Category : Science
ISBN : 9781139463874

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Bayesian Methods for Ecology by Michael A. McCarthy Pdf

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.

Bayesian Analysis for Population Ecology

Ruth King,Byron Morgan,Olivier Gimenez,Steve Brooks
Bayesian Analysis for Population Ecology Book PDF

Author : Ruth King,Byron Morgan,Olivier Gimenez,Steve Brooks
Publisher : CRC Press
Page : 457 pages
File Size : 48,5 Mb
Release : 2009-10-30
Category : Mathematics
ISBN : 9781439811887

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Bayesian Analysis for Population Ecology by Ruth King,Byron Morgan,Olivier Gimenez,Steve Brooks Pdf

Novel Statistical Tools for Conserving and Managing PopulationsBy gathering information on key demographic parameters, scientists can often predict how populations will develop in the future and relate these parameters to external influences, such as global warming. Because of their ability to easily incorporate random effects, fit state-space mode

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt
Bayesian Data Analysis in Ecology Using Linear Models with R BUGS and Stan Book PDF

Author : Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt
Publisher : Academic Press
Page : 328 pages
File Size : 51,7 Mb
Release : 2015-04-04
Category : Science
ISBN : 9780128016787

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Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan by Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt Pdf

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

Bayesian Inference

William A Link,Richard J Barker
Bayesian Inference Book PDF

Author : William A Link,Richard J Barker
Publisher : Academic Press
Page : 354 pages
File Size : 41,7 Mb
Release : 2009-08-07
Category : Science
ISBN : 9780080889801

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Bayesian Inference by William A Link,Richard J Barker Pdf

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

Bayesian Methods for Ecology

Michael A. McCarthy
Bayesian Methods for Ecology Book PDF

Author : Michael A. McCarthy
Publisher : Unknown
Page : 312 pages
File Size : 46,6 Mb
Release : 2007
Category : Bayesian statistical decision theory
ISBN : 0511284942

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Bayesian Methods for Ecology by Michael A. McCarthy Pdf

An accessible text describing how to use Bayesian methods of statistical analysis in ecology.

Introduction to Bayesian Methods in Ecology and Natural Resources

Edwin J. Green,Andrew O. Finley,William E. Strawderman
Introduction to Bayesian Methods in Ecology and Natural Resources Book PDF

Author : Edwin J. Green,Andrew O. Finley,William E. Strawderman
Publisher : Springer Nature
Page : 188 pages
File Size : 42,8 Mb
Release : 2020-11-26
Category : Science
ISBN : 9783030607500

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Introduction to Bayesian Methods in Ecology and Natural Resources by Edwin J. Green,Andrew O. Finley,William E. Strawderman Pdf

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.

Likelihood Methods in Biology and Ecology

Michael Brimacombe
Likelihood Methods in Biology and Ecology Book PDF

Author : Michael Brimacombe
Publisher : CRC Press
Page : 304 pages
File Size : 54,8 Mb
Release : 2018-12-18
Category : Mathematics
ISBN : 9780429533235

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Likelihood Methods in Biology and Ecology by Michael Brimacombe Pdf

This book emphasizes the importance of the likelihood function in statistical theory and applications and discusses it in the context of biology and ecology. Bayesian and frequentist methods both use the likelihood function and provide differing but related insights. This is examined here both through review of basic methodology and also the integr

Hierarchical Modeling and Inference in Ecology

J. Andrew Royle,Robert M. Dorazio
Hierarchical Modeling and Inference in Ecology Book PDF

Author : J. Andrew Royle,Robert M. Dorazio
Publisher : Elsevier
Page : 464 pages
File Size : 40,6 Mb
Release : 2008-10-15
Category : Science
ISBN : 9780080559254

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Hierarchical Modeling and Inference in Ecology by J. Andrew Royle,Robert M. Dorazio Pdf

A guide to data collection, modeling and inference strategies for biological survey data using Bayesian and classical statistical methods. This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models, with a strict focus on the use of probability models and parametric inference. Hierarchical models represent a paradigm shift in the application of statistics to ecological inference problems because they combine explicit models of ecological system structure or dynamics with models of how ecological systems are observed. The principles of hierarchical modeling are developed and applied to problems in population, metapopulation, community, and metacommunity systems. The book provides the first synthetic treatment of many recent methodological advances in ecological modeling and unifies disparate methods and procedures. The authors apply principles of hierarchical modeling to ecological problems, including * occurrence or occupancy models for estimating species distribution * abundance models based on many sampling protocols, including distance sampling * capture-recapture models with individual effects * spatial capture-recapture models based on camera trapping and related methods * population and metapopulation dynamic models * models of biodiversity, community structure and dynamics * Wide variety of examples involving many taxa (birds, amphibians, mammals, insects, plants) * Development of classical, likelihood-based procedures for inference, as well as Bayesian methods of analysis * Detailed explanations describing the implementation of hierarchical models using freely available software such as R and WinBUGS * Computing support in technical appendices in an online companion web site

Bayesian Models

N. Thompson Hobbs,Mevin Hooten
Bayesian Models Book PDF

Author : N. Thompson Hobbs,Mevin Hooten
Publisher : Princeton University Press
Page : 315 pages
File Size : 50,8 Mb
Release : 2015-08-04
Category : Science
ISBN : 9781400866557

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Bayesian Models by N. Thompson Hobbs,Mevin Hooten Pdf

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

Introduction to Hierarchical Bayesian Modeling for Ecological Data

Eric Parent,Etienne Rivot
Introduction to Hierarchical Bayesian Modeling for Ecological Data Book PDF

Author : Eric Parent,Etienne Rivot
Publisher : CRC Press
Page : 429 pages
File Size : 53,7 Mb
Release : 2012-08-21
Category : Mathematics
ISBN : 9781584889199

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Introduction to Hierarchical Bayesian Modeling for Ecological Data by Eric Parent,Etienne Rivot Pdf

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 statistical models. The text begins with simple models that progressively become more complex and realistic through explanatory covariates and intermediate hidden states variables. When fitting the models to data, the authors gradually present the concepts and techniques of the Bayesian paradigm from a practical point of view using real case studies. They emphasize how hierarchical Bayesian modeling supports multidimensional models involving complex interactions between parameters and latent variables. Data sets, exercises, and R and WinBUGS codes are available on the authors’ website. This book shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competing hypotheses, and assess degrees of confidence of predictions. It also illustrates how conditional reasoning can dismantle a complex reality into more understandable pieces. As conditional reasoning is intimately linked with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling, estimation, and prediction.

Introduction to WinBUGS for Ecologists

Marc Kery
Introduction to WinBUGS for Ecologists Book PDF

Author : Marc Kery
Publisher : Academic Press
Page : 320 pages
File Size : 53,9 Mb
Release : 2010-07-19
Category : Science
ISBN : 0123786061

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Introduction to WinBUGS for Ecologists by Marc Kery Pdf

Introduction to WinBUGS for Ecologists introduces applied Bayesian modeling to ecologists using the highly acclaimed, free WinBUGS software. It offers an understanding of statistical models as abstract representations of the various processes that give rise to a data set. Such an understanding is basic to the development of inference models tailored to specific sampling and ecological scenarios. The book begins by presenting the advantages of a Bayesian approach to statistics and introducing the WinBUGS software. It reviews the four most common statistical distributions: the normal, the uniform, the binomial, and the Poisson. It describes the two different kinds of analysis of variance (ANOVA): one-way and two- or multiway. It looks at the general linear model, or ANCOVA, in R and WinBUGS. It introduces generalized linear model (GLM), i.e., the extension of the normal linear model to allow error distributions other than the normal. The GLM is then extended contain additional sources of random variation to become a generalized linear mixed model (GLMM) for a Poisson example and for a binomial example. The final two chapters showcase two fairly novel and nonstandard versions of a GLMM. The first is the site-occupancy model for species distributions; the second is the binomial (or N-) mixture model for estimation and modeling of abundance. Introduction to the essential theories of key models used by ecologists Complete juxtaposition of classical analyses in R and Bayesian analysis of the same models in WinBUGS Provides every detail of R and WinBUGS code required to conduct all analyses Companion Web Appendix that contains all code contained in the book and additional material (including more code and solutions to exercises)

Ecological Models and Data in R

Benjamin M. Bolker
Ecological Models and Data in R Book PDF

Author : Benjamin M. Bolker
Publisher : Princeton University Press
Page : 408 pages
File Size : 41,5 Mb
Release : 2008-07-21
Category : Computers
ISBN : 9780691125220

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Ecological Models and Data in R by Benjamin M. Bolker Pdf

Introduction and background; Exploratory data analysis and graphics; Deterministic functions for ecological modeling; Probability and stochastic distributions for ecological modeling; Stochatsic simulation and power analysis; Likelihood and all that; Optimization and all that; Likelihood examples; Standar statistics revisited; Modeling variance; Dynamic models.

Bayesian Data Analysis, Third Edition

Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Bayesian Data Analysis Third Edition Book PDF

Author : Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin
Publisher : CRC Press
Page : 677 pages
File Size : 42,8 Mb
Release : 2013-11-01
Category : Mathematics
ISBN : 9781439840955

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Bayesian Data Analysis, Third Edition by Andrew Gelman,John B. Carlin,Hal S. Stern,David B. Dunson,Aki Vehtari,Donald B. Rubin Pdf

Now in its third edition, this classic book is widely considered the leading text on Bayesian methods, lauded for its accessible, practical approach to analyzing data and solving research problems. Bayesian Data Analysis, Third Edition continues to take an applied approach to analysis using up-to-date Bayesian methods. The authors—all leaders in the statistics community—introduce basic concepts from a data-analytic perspective before presenting advanced methods. Throughout the text, numerous worked examples drawn from real applications and research emphasize the use of Bayesian inference in practice. New to the Third Edition Four new chapters on nonparametric modeling Coverage of weakly informative priors and boundary-avoiding priors Updated discussion of cross-validation and predictive information criteria Improved convergence monitoring and effective sample size calculations for iterative simulation Presentations of Hamiltonian Monte Carlo, variational Bayes, and expectation propagation New and revised software code The book can be used in three different ways. For undergraduate students, it introduces Bayesian inference starting from first principles. For graduate students, the text presents effective current approaches to Bayesian modeling and computation in statistics and related fields. For researchers, it provides an assortment of Bayesian methods in applied statistics. Additional materials, including data sets used in the examples, solutions to selected exercises, and software instructions, are available on the book’s web page.

Bringing Bayesian Models to Life

Mevin B. Hooten,Trevor Hefley
Bringing Bayesian Models to Life Book PDF

Author : Mevin B. Hooten,Trevor Hefley
Publisher : CRC Press
Page : 591 pages
File Size : 44,6 Mb
Release : 2019-05-15
Category : Science
ISBN : 9780429513374

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Bringing Bayesian Models to Life by Mevin B. Hooten,Trevor Hefley Pdf

Bringing Bayesian Models to Life empowers the reader to extend, enhance, and implement statistical models for ecological and environmental data analysis. We open the black box and show the reader how to connect modern statistical models to computer algorithms. These algorithms allow the user to fit models that answer their scientific questions without needing to rely on automated Bayesian software. We show how to handcraft statistical models that are useful in ecological and environmental science including: linear and generalized linear models, spatial and time series models, occupancy and capture-recapture models, animal movement models, spatio-temporal models, and integrated population-models. Features: R code implementing algorithms to fit Bayesian models using real and simulated data examples. A comprehensive review of statistical models commonly used in ecological and environmental science. Overview of Bayesian computational methods such as importance sampling, MCMC, and HMC. Derivations of the necessary components to construct statistical algorithms from scratch. Bringing Bayesian Models to Life contains a comprehensive treatment of models and associated algorithms for fitting the models to data. We provide detailed and annotated R code in each chapter and apply it to fit each model we present to either real or simulated data for instructional purposes. Our code shows how to create every result and figure in the book so that readers can use and modify it for their own analyses. We provide all code and data in an organized set of directories available at the authors' websites.

Bayesian Statistics for Beginners

Therese M. Donovan,Ruth M. Mickey
Bayesian Statistics for Beginners Book PDF

Author : Therese M. Donovan,Ruth M. Mickey
Publisher : Oxford University Press, USA
Page : 430 pages
File Size : 47,7 Mb
Release : 2019
Category : Mathematics
ISBN : 9780198841296

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Bayesian Statistics for Beginners by Therese M. Donovan,Ruth M. Mickey Pdf

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.