Introduction to WinBUGS for Ecologists

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)

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  • Author : Marc Kery
  • Publisher : Academic Press
  • Pages : 320 pages
  • ISBN : 9780123786067
  • Rating : 5/5 from 1 reviews
CLICK HERE TO GET THIS BOOKIntroduction to WinBUGS for Ecologists

Introduction to WinBUGS for Ecologists

Introduction to WinBUGS for Ecologists
  • Author : Marc Kery
  • Publisher : Academic Press
  • Release : 19 July 2010
GET THIS BOOKIntroduction to WinBUGS for Ecologists

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

Bayesian Population Analysis Using WinBUGS

Bayesian Population Analysis Using WinBUGS
  • Author : Marc Kéry,Michael Schaub
  • Publisher : Academic Press
  • Release : 25 June 2022
GET THIS BOOKBayesian Population Analysis Using WinBUGS

Bayesian statistics has exploded into biology and its sub-disciplines, such as ecology, over the past decade. The free software program WinBUGS, and its open-source sister OpenBugs, is currently the only flexible and general-purpose program available with which the average ecologist can conduct standard and non-standard Bayesian statistics. Comprehensive and richly commented examples illustrate a wide range of models that are most relevant to the research of a modern population ecologist All WinBUGS/OpenBUGS analyses are completely integrated in software R

Spatial Capture-Recapture

Spatial Capture-Recapture
  • Author : J. Andrew Royle,Richard B. Chandler,Rahel Sollmann,Beth Gardner
  • Publisher : Academic Press
  • Release : 27 August 2013
GET THIS BOOKSpatial Capture-Recapture

Spatial Capture-Recapture provides a comprehensive how-to manual with detailed examples of spatial capture-recapture models based on current technology and knowledge. Spatial Capture-Recapture provides you with an extensive step-by-step analysis of many data sets using different software implementations. The authors' approach is practical – it embraces Bayesian and classical inference strategies to give the reader different options to get the job done. In addition, Spatial Capture-Recapture provides data sets, sample code and computing scripts in an R package. Comprehensive reference on revolutionary

Bayesian Methods for Ecology

Bayesian Methods for Ecology
  • Author : Michael A. McCarthy
  • Publisher : Cambridge University Press
  • Release : 10 May 2007
GET THIS BOOKBayesian Methods for Ecology

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.

Bayesian Analysis for Population Ecology

Bayesian Analysis for Population Ecology
  • Author : Ruth King,Byron Morgan,Olivier Gimenez,Steve Brooks
  • Publisher : CRC Press
  • Release : 30 October 2009
GET THIS BOOKBayesian Analysis for Population Ecology

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

Integrated Population Models

Integrated Population Models
  • Author : Michael Schaub,Marc Kery
  • Publisher : Academic Press
  • Release : 23 November 2021
GET THIS BOOKIntegrated Population Models

Integrated Population Models: Theory and Ecological Applications with R and JAGS is the first book on integrated population models, which constitute a powerful framework for combining multiple data sets from the population and the individual levels to estimate demographic parameters, and population size and trends. These models identify drivers of population dynamics and forecast the composition and trajectory of a population. Written by two population ecologists with expertise on integrated population modeling, this book provides a comprehensive synthesis of the

Introduction to Bayesian Methods in Ecology and Natural Resources

Introduction to Bayesian Methods in Ecology and Natural Resources
  • Author : Edwin J. Green,Andrew O. Finley,William E. Strawderman
  • Publisher : Springer Nature
  • Release : 26 November 2020
GET THIS BOOKIntroduction to Bayesian Methods in Ecology and Natural Resources

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,

Ecological Models and Data in R

Ecological Models and Data in R
  • Author : Benjamin M. Bolker
  • Publisher : Princeton University Press
  • Release : 21 July 2008
GET THIS BOOKEcological Models and Data in R

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.

Analysis and Management of Animal Populations

Analysis and Management of Animal Populations
  • Author : Byron K. Williams,James D. Nichols,Michael J. Conroy
  • Publisher : Academic Press
  • Release : 01 May 2002
GET THIS BOOKAnalysis and Management of Animal Populations

Analysis and Management of Animal Populations deals with the processes involved in making informed decisions about the management of animal populations. It covers the modeling of population responses to management actions, the estimation of quantities needed in the modeling effort, and the application of these estimates and models to the development of sound management decisions. The book synthesizes and integrates in a single volume the methods associated with these themes, as they apply to ecological assessment and conservation of animal

Introduction to Hierarchical Bayesian Modeling for Ecological Data

Introduction to Hierarchical Bayesian Modeling for Ecological Data
  • Author : Eric Parent,Etienne Rivot
  • Publisher : CRC Press
  • Release : 21 August 2012
GET THIS BOOKIntroduction to Hierarchical Bayesian Modeling for Ecological Data

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

Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS

Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS
  • Author : Marc Kery,J. Andrew Royle
  • Publisher : Academic Press
  • Release : 14 November 2015
GET THIS BOOKApplied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS

Applied Hierarchical Modeling in Ecology: Distribution, Abundance, Species Richness offers a new synthesis of the state-of-the-art of hierarchical models for plant and animal distribution, abundance, and community characteristics such as species richness using data collected in metapopulation designs. These types of data are extremely widespread in ecology and its applications in such areas as biodiversity monitoring and fisheries and wildlife management. This first volume explains static models/procedures in the context of hierarchical models that collectively represent a unified approach

Introduction to Bayesian Methods in Ecology and Natural Resources

Introduction to Bayesian Methods in Ecology and Natural Resources
  • Author : Edwin J. Green,Andrew O. Finley,William E. Strawderman
  • Publisher : Springer
  • Release : 27 November 2021
GET THIS BOOKIntroduction to Bayesian Methods in Ecology and Natural Resources

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,

Hierarchical Modeling and Inference in Ecology

Hierarchical Modeling and Inference in Ecology
  • Author : J. Andrew Royle,Robert M. Dorazio
  • Publisher : Elsevier
  • Release : 15 October 2008
GET THIS BOOKHierarchical Modeling and Inference in Ecology

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

Mixed Effects Models and Extensions in Ecology with R

Mixed Effects Models and Extensions in Ecology with R
  • Author : Alain Zuur,Elena N. Ieno,Neil Walker,Anatoly A. Saveliev,Graham M. Smith
  • Publisher : Springer Science & Business Media
  • Release : 05 March 2009
GET THIS BOOKMixed Effects Models and Extensions in Ecology with R

This book discusses advanced statistical methods that can be used to analyse ecological data. Most environmental collected data are measured repeatedly over time, or space and this requires the use of GLMM or GAMM methods. The book starts by revising regression, additive modelling, GAM and GLM, and then discusses dealing with spatial or temporal dependencies and nested data.

Bayesian Models

Bayesian Models
  • Author : N. Thompson Hobbs,Mevin B. Hooten
  • Publisher : Princeton University Press
  • Release : 04 August 2015
GET THIS BOOKBayesian Models

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