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6 produkter
6 produkter
E-bok
Engelska, 2010504 kr
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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)
E-bok
Engelska, 2011687 kr
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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
E-bok
Engelska, 2015945 kr
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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 to ecological research, taking the reader from design, through data collection, and into analyses using a very powerful class of models. Applied Hierarchical Modeling in Ecology, Volume 1 serves as an indispensable manual for practicing field biologists, and as a graduate-level text for students in ecology, conservation biology, fisheries/wildlife management, and related fields.- Provides a synthesis of important classes of models about distribution, abundance, and species richness while accommodating imperfect detection- Presents models and methods for identifying unmarked individuals and species- Written in a step-by-step approach accessible to non-statisticians and provides fully worked examples that serve as a template for readers'' analyses- Includes companion website containing data sets, code, solutions to exercises, and further information
E-bok
Engelska, 20201 322 kr
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Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS, Volume Two: Dynamic and Advanced Models provides a synthesis of the state-of-the-art in hierarchical models for plant and animal distribution, also focusing on the complex and more advanced models currently available. The book explains all procedures in the context of hierarchical models that represent a unified approach to ecological research, thus taking the reader from design, through data collection, and into analyses using a very powerful way of synthesizing data.- Makes ecological modeling accessible to people who are struggling to use complex or advanced modeling programs- Synthesizes current ecological models and explains how they are inter-connected- Contains numerous examples throughout the book, walking the reading through scenarios with both real and simulated data- Provides an ideal resource for ecologists working in R software and in BUGS software for more flexible Bayesian analyses
1 648 kr
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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 relevant theory of integrated population models with an extensive overview of practical applications, using Bayesian methods by means of case studies. The book contains fully-documented, complete code for fitting all models in the free software, R and JAGS. It also includes all required code for pre- and post-model-fitting analysis.Integrated Population Models is an invaluable reference for researchers and practitioners involved in population analysis, and for graduate-level students in ecology, conservation biology, wildlife management, and related fields. The text is ideal for self-study and advanced graduate-level courses.- Offers practical and accessible ecological applications of IPMs (integrated population models)- Provides full documentation of analyzed code in the Bayesian framework- Written and structured for an easy approach to the subject, especially for non-statisticians
E-bok
Engelska, 20241 185 kr
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**2025 PROSE Award Finalist in Environmental Science**Applied Statistical Modelling for Ecologists provides a gentle introduction to the essential models of applied statistics: linear models, generalized linear models, mixed and hierarchical models. All models are fit with both a likelihood and a Bayesian approach, using several powerful software packages widely used in research publications: JAGS, NIMBLE, Stan, and TMB. In addition, the foundational method of maximum likelihood is explained in a manner that ecologists can really understand.This book is the successor of the widely used Introduction to WinBUGS for Ecologists (Kéry, Academic Press, 2010). Like its parent, it is extremely effective for both classroom use and self-study, allowing students and researchers alike to quickly learn, understand, and carry out a very wide range of statistical modelling tasks.The examples in Applied Statistical Modelling for Ecologists come from ecology and the environmental sciences, but the underlying statistical models are very widely used by scientists across many disciplines. This book will be useful for anybody who needs to learn and quickly become proficient in statistical modelling, with either a likelihood or a Bayesian focus, and in the model-fitting engines covered, including the three latest packages NIMBLE, Stan, and TMB.- Contains a concise and gentle introduction to probability and applied statistics as needed in ecology and the environmental sciences- Covers the foundations of modern applied statistical modelling- Gives a comprehensive, applied introduction to what currently are the most widely used and most exciting, cutting-edge model fitting software packages: JAGS, NIMBLE, Stan, and TMB- Provides a highly accessible applied introduction to the two dominant methods of fitting parametric statistical models: maximum likelihood and Bayesian posterior inference- Details the principles of model building, model checking and model selection- Adopts a "Rosetta Stone" approach, wherein understanding of one software, and of its associated language, will be greatly enhanced by seeing the analogous code in other engines- Provides all code available for download for students, at https://www.elsevier.com/books-and-journals/book-companion/9780443137150