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

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

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  • Author : Franzi Korner-Nievergelt
  • Publisher : Academic Press
  • Pages : 328 pages
  • ISBN : 0128016787
  • Rating : 4/5 from 21 reviews
CLICK HERE TO GET THIS BOOKBayesian Data Analysis in Ecology Using Linear Models with R BUGS and Stan

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

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan
  • Author : Franzi Korner-Nievergelt,Tobias Roth,Stefanie von Felten,Jérôme Guélat,Bettina Almasi,Pius Korner-Nievergelt
  • Publisher : Academic Press
  • Release : 04 April 2015
GET THIS BOOKBayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

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

Spatial Data Analysis in Ecology and Agriculture Using R, Second Edition

Spatial Data Analysis in Ecology and Agriculture Using R, Second Edition
  • Author : Richard E. Plant
  • Publisher : CRC Press
  • Release : 07 December 2018
GET THIS BOOKSpatial Data Analysis in Ecology and Agriculture Using R, Second Edition

Key features: Unique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using R Provides exercises in each chapter to facilitate the book's use as a course textbook or for self-study Adds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data. Includes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methods Updates its coverage of

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

Handbook of Mixture Analysis

Handbook of Mixture Analysis
  • Author : Sylvia Fruhwirth-Schnatter,Gilles Celeux,Christian P. Robert
  • Publisher : CRC Press
  • Release : 04 January 2019
GET THIS BOOKHandbook of Mixture Analysis

Mixture models have been around for over 150 years, and they are found in many branches of statistical modelling, as a versatile and multifaceted tool. They can be applied to a wide range of data: univariate or multivariate, continuous or categorical, cross-sectional, time series, networks, and much more. Mixture analysis is a very active research topic in statistics and machine learning, with new developments in methodology and applications taking place all the time. The Handbook of Mixture Analysis is a very

Protection Strategy against Spruce Budworm

Protection Strategy against Spruce Budworm
  • Author : David A. MacLean
  • Publisher : MDPI
  • Release : 15 January 2020
GET THIS BOOKProtection Strategy against Spruce Budworm

Spruce budworm (Choristoneura fumiferana (Clem.)) outbreaks are a dominant natural disturbance in the forests of Canada and northeastern USA. Widespread, severe defoliation by this native insect results in large-scale mortality and growth reductions of spruce (Picea sp.) and balsam fir (Abies balsamea (L.) Mill.) forests, and largely determines future age–class structure and productivity. The last major spruce budworm outbreak defoliated over 58 million hectares in the 1970s–1980s, and caused 32–43 million m3/year of timber volume losses from 1978 to 1987, in

The New Statistics with R

The New Statistics with R
  • Author : Andy Hector
  • Publisher : Oxford University Press
  • Release : 17 June 2021
GET THIS BOOKThe New Statistics with R

A proven textbook based on materials developed over the last decade to teach linear, generalized, and mixed model analysis to students of ecology, evolution, and environmental studies. While R is used throughout, the focus is firmly on statistical analysis.

Diversity, Freedom and Evolution

Diversity, Freedom and Evolution
  • Author : Anonim
  • Publisher : Cambridge Scholars Publishing
  • Release : 22 March 2019
GET THIS BOOKDiversity, Freedom and Evolution

Science is responsible for most of the miracles that define modern life. This leads to the disconcerting situation where need and belief are in conflict. There is an enormous literature about science and evolution in particular, but all previous authors have missed the point that evolution gives us basic tenets that are not situation- or culture-dependent. This book shows that the potential for evolution is based on the tenets of diversity and freedom, which also underlie most of the ethical

The Adaptive Value of Languages: Non-Linguistic Causes of Language Diversity

The Adaptive Value of Languages: Non-Linguistic Causes of Language Diversity
  • Author : Antonio Benítez-Burraco,Steven Moran
  • Publisher : Frontiers Media SA
  • Release : 08 November 2018
GET THIS BOOKThe Adaptive Value of Languages: Non-Linguistic Causes of Language Diversity

The goal of this eBook is to shed light on the non-linguistic causes of language diversity, and in particular, to explore the possibility that some aspects of the structure of languages may result from an adaptation to the natural and/or human-made environment. Traditionally, language diversity has been claimed to result from random, internally-motivated changes in language structure. However, ongoing research suggests instead that different factors that are external to language can promote language change and ultimately account for aspects

Statistical Rethinking

Statistical Rethinking
  • Author : Richard McElreath
  • Publisher : CRC Press
  • Release : 03 January 2018
GET THIS BOOKStatistical Rethinking

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on

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.

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

Doing Bayesian Data Analysis

Doing Bayesian Data Analysis
  • Author : John Kruschke
  • Publisher : Academic Press
  • Release : 11 November 2014
GET THIS BOOKDoing Bayesian Data Analysis

Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian data analysis, as material is explained clearly with concrete examples. Included are step-by-step instructions on how to carry out Bayesian data analyses in the popular and free software R and WinBugs, as well as new programs in JAGS and Stan. The new programs are designed to be much easier to use than the scripts in the first edition. In particular,