Bayesian 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 Includes complete documentation of all R and WinBUGS code required to conduct analyses and shows all the necessary steps from having the data in a text file out of Excel to interpreting and processing the output from WinBUGS in R

Produk Detail:

  • Author : Marc Kéry
  • Publisher : Academic Press
  • Pages : 535 pages
  • ISBN : 0123870208
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBayesian Population Analysis Using WinBUGS

Bayesian Population Analysis Using WinBUGS

Bayesian Population Analysis Using WinBUGS
  • Author : Marc Kéry,Michael Schaub
  • Publisher : Academic Press
  • Release : 23 July 2021
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

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

Integrated Population Models

Integrated Population Models
  • Author : Michael Schaub,Marc Kéry
  • Publisher : Academic Press
  • Release : 15 July 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

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

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.

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

Bayesian Modeling Using WinBUGS

Bayesian Modeling Using WinBUGS
  • Author : Ioannis Ntzoufras
  • Publisher : John Wiley & Sons
  • Release : 20 September 2011
GET THIS BOOKBayesian Modeling Using WinBUGS

A hands-on introduction to the principles of Bayesian modeling using WinBUGS Bayesian Modeling Using WinBUGS provides an easily accessible introduction to the use of WinBUGS programming techniques in a variety of Bayesian modeling settings. The author provides an accessible treatment of the topic, offering readers a smooth introduction to the principles of Bayesian modeling with detailed guidance on the practical implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes

The BUGS Book

The BUGS Book
  • Author : David Lunn,Chris Jackson,Nicky Best,Andrew Thomas,David Spiegelhalter
  • Publisher : CRC Press
  • Release : 02 October 2012
GET THIS BOOKThe BUGS Book

Bayesian statistical methods have become widely used for data analysis and modelling in recent years, and the BUGS software has become the most popular software for Bayesian analysis worldwide. Authored by the team that originally developed this software, The BUGS Book provides a practical introduction to this program and its use. The text presents complete coverage of all the functionalities of BUGS, including prediction, missing data, model criticism, and prior sensitivity. It also features a large number of worked examples

Studyguide for Bayesian Population Analysis Using Winbugs

Studyguide for Bayesian Population Analysis Using Winbugs
  • Author : Cram101 Textbook Reviews
  • Publisher : Cram101
  • Release : 01 May 2013
GET THIS BOOKStudyguide for Bayesian Population Analysis Using Winbugs

Never HIGHLIGHT a Book Again Includes all testable terms, concepts, persons, places, and events. Cram101 Just the FACTS101 studyguides gives all of the outlines, highlights, and quizzes for your textbook with optional online comprehensive practice tests. Only Cram101 is Textbook Specific. Accompanies: 9780872893795. This item is printed on demand.

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

Bayesian Methods for Statistical Analysis

Bayesian Methods for Statistical Analysis
  • Author : Borek Puza
  • Publisher : ANU Press
  • Release : 01 October 2015
GET THIS BOOKBayesian Methods for Statistical Analysis

Bayesian Methods for Statistical Analysis is a book on statistical methods for analysing a wide variety of data. The book consists of 12 chapters, starting with basic concepts and covering numerous topics, including Bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, Markov chain Monte Carlo methods, finite population inference, biased sampling and nonignorable nonresponse. The book contains many exercises, all with worked solutions, including complete computer code. It is suitable for self-study or a semester-long course, with three hours of

Introduction to Probability Simulation and Gibbs Sampling with R

Introduction to Probability Simulation and Gibbs Sampling with R
  • Author : Eric A. Suess,Bruce E. Trumbo
  • Publisher : Springer Science & Business Media
  • Release : 15 June 2010
GET THIS BOOKIntroduction to Probability Simulation and Gibbs Sampling with R

The first seven chapters use R for probability simulation and computation, including random number generation, numerical and Monte Carlo integration, and finding limiting distributions of Markov Chains with both discrete and continuous states. Applications include coverage probabilities of binomial confidence intervals, estimation of disease prevalence from screening tests, parallel redundancy for improved reliability of systems, and various kinds of genetic modeling. These initial chapters can be used for a non-Bayesian course in the simulation of applied probability models and Markov

Bayesian Ideas and Data Analysis

Bayesian Ideas and Data Analysis
  • Author : Ronald Christensen,Wesley Johnson,Adam Branscum,Timothy E Hanson
  • Publisher : CRC Press
  • Release : 07 July 2011
GET THIS BOOKBayesian Ideas and Data Analysis

Emphasizing the use of WinBUGS and R to analyze real data, Bayesian Ideas and Data Analysis: An Introduction for Scientists and Statisticians presents statistical tools to address scientific questions. It highlights foundational issues in statistics, the importance of making accurate predictions, and the need for scientists and statisticians to collaborate in analyzing data. The WinBUGS code provided offers a convenient platform to model and analyze a wide range of data. The first five chapters of the book contain core material

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