Bayesian Data Analysis In Ecology Using Linear Models With R Bugs And Stan

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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 : 54,7 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 Models for Astrophysical Data

Joseph M. Hilbe,Rafael S. de Souza,Emille E. O. Ishida
Bayesian Models for Astrophysical Data Book PDF

Author : Joseph M. Hilbe,Rafael S. de Souza,Emille E. O. Ishida
Publisher : Cambridge University Press
Page : 429 pages
File Size : 51,5 Mb
Release : 2017-04-27
Category : Mathematics
ISBN : 9781107133082

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Bayesian Models for Astrophysical Data by Joseph M. Hilbe,Rafael S. de Souza,Emille E. O. Ishida Pdf

A hands-on guide to Bayesian models with R, JAGS, Python, and Stan code, for a wide range of astronomical data types.

Spatial Data Analysis in Ecology and Agriculture Using R

Richard E. Plant
Spatial Data Analysis in Ecology and Agriculture Using R Book PDF

Author : Richard E. Plant
Publisher : CRC Press
Page : 689 pages
File Size : 50,8 Mb
Release : 2018-12-07
Category : Science
ISBN : 9781351189897

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Spatial Data Analysis in Ecology and Agriculture Using R by Richard E. Plant Pdf

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 R software including newly introduced packages Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presenting and explaining R code, aspects maintained in this update. Using data sets from cultivated and uncultivated ecosystems, the book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Additional material to accompany the book, on both analyzing satellite data and on multivariate analysis, can be accessed at https://www.plantsciences.ucdavis.edu/plant/additionaltopics.htm.

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

Marc Kéry,J. Andrew Royle
Applied Hierarchical Modeling in Ecology Analysis of distribution abundance and species richness in R and BUGS Book PDF

Author : Marc Kéry,J. Andrew Royle
Publisher : Academic Press
Page : 810 pages
File Size : 55,6 Mb
Release : 2015-11-14
Category : Science
ISBN : 9780128014868

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Applied Hierarchical Modeling in Ecology: Analysis of distribution, abundance and species richness in R and BUGS by Marc Kéry,J. Andrew Royle Pdf

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

Advancements in Bayesian Methods and Implementations

Anonim
Advancements in Bayesian Methods and Implementations Book PDF

Author : Anonim
Publisher : Academic Press
Page : 322 pages
File Size : 43,5 Mb
Release : 2022-10-06
Category : Mathematics
ISBN : 9780323952699

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Advancements in Bayesian Methods and Implementations by Anonim Pdf

Advancements in Bayesian Methods and Implementation, Volume 47 in the Handbook of Statistics series, highlights new advances in the field, with this new volume presenting interesting chapters on a variety of timely topics, including Fisher Information, Cramer-Rao and Bayesian Paradigm, Compound beta binomial distribution functions, MCMC for GLMMS, Signal Processing and Bayesian, Mathematical theory of Bayesian statistics where all models are wrong, Machine Learning and Bayesian, Non-parametric Bayes, Bayesian testing, and Data Analysis with humans, Variational inference or Functional horseshoe, Generalized Bayes. Provides the authority and expertise of leading contributors from an international board of authors Presents the latest release in the Handbook of Statistics series Updated release includes the latest information on Advancements in Bayesian Methods and Implementation

Handbook of Mixture Analysis

Sylvia Fruhwirth-Schnatter,Gilles Celeux,Christian P. Robert
Handbook of Mixture Analysis Book PDF

Author : Sylvia Fruhwirth-Schnatter,Gilles Celeux,Christian P. Robert
Publisher : CRC Press
Page : 388 pages
File Size : 52,7 Mb
Release : 2019-01-04
Category : Computers
ISBN : 9780429508868

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Handbook of Mixture Analysis by Sylvia Fruhwirth-Schnatter,Gilles Celeux,Christian P. Robert Pdf

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 timely publication, presenting a broad overview of the methods and applications of this important field of research. It covers a wide array of topics, including the EM algorithm, Bayesian mixture models, model-based clustering, high-dimensional data, hidden Markov models, and applications in finance, genomics, and astronomy. Features: Provides a comprehensive overview of the methods and applications of mixture modelling and analysis Divided into three parts: Foundations and Methods; Mixture Modelling and Extensions; and Selected Applications Contains many worked examples using real data, together with computational implementation, to illustrate the methods described Includes contributions from the leading researchers in the field The Handbook of Mixture Analysis is targeted at graduate students and young researchers new to the field. It will also be an important reference for anyone working in this field, whether they are developing new methodology, or applying the models to real scientific problems.

Statistical Rethinking

Richard McElreath
Statistical Rethinking Book PDF

Author : Richard McElreath
Publisher : CRC Press
Page : 489 pages
File Size : 40,7 Mb
Release : 2018-01-03
Category : Mathematics
ISBN : 9781482253481

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Statistical Rethinking by Richard McElreath Pdf

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 a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Integrated Population Models

Michael Schaub,Marc Kéry
Integrated Population Models Book PDF

Author : Michael Schaub,Marc Kéry
Publisher : Academic Press
Page : 640 pages
File Size : 40,7 Mb
Release : 2021-11-12
Category : Science
ISBN : 9780128209158

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Integrated Population Models by Michael Schaub,Marc Kéry Pdf

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

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 : 48,5 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.

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 : 50,5 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)

Protection Strategy against Spruce Budworm

David A. MacLean
Protection Strategy against Spruce Budworm Book PDF

Author : David A. MacLean
Publisher : MDPI
Page : 220 pages
File Size : 52,9 Mb
Release : 2020-01-15
Category : Science
ISBN : 9783039280964

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Protection Strategy against Spruce Budworm by David A. MacLean Pdf

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 Canada. Management to deal with spruce budworm outbreaks has emphasized forest protection, spraying registered insecticides to prevent defoliation and keep trees alive. Other tactics can include salvage harvesting, altering harvest schedules to remove the most susceptible stands, or reducing future susceptibility by planting or thinning. Chemical insecticides are no longer used, and protection strategies use biological insecticides Bacillus thuringiensis (B.t.) or tebufenozide, a specific insect growth regulator. Over the last five years, a $30 million research project has tested another possible management tactic, termed an ‘early intervention strategy’, aimed at area-wide management of spruce budworm populations. This includes intensive monitoring to detect ‘hot spots’ of rising budworm populations before defoliation occurs, targeted insecticide treatment to prevent spread, and detailed research into target and non-target insect effects. The objective of this Special Issue is to compile the most recent research on protection strategies against spruce budworm. A series of papers will describe results and prospects for the use of an early intervention strategy in spruce budworm and other insect management.

Explorations in Empirical Translation Process Research

Michael Carl
Explorations in Empirical Translation Process Research Book PDF

Author : Michael Carl
Publisher : Springer Nature
Page : 436 pages
File Size : 45,5 Mb
Release : 2021-07-27
Category : Language Arts & Disciplines
ISBN : 9783030697778

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Explorations in Empirical Translation Process Research by Michael Carl Pdf

This book assembles fifteen original, interdisciplinary research chapters that explore methodological and conceptual considerations as well as user and usage studies to elucidate the relation between the translation product and translation/post-editing processes. It introduces numerous innovative empirical/data-driven measures as well as novel classification schemes and taxonomies to investigate and quantify the relation between translation quality and translation effort in from-scratch translation, machine translation post-editing and computer-assisted audiovisual translation. The volume addresses questions in the translation of cognates, neologisms, metaphors, and idioms, as well as figurative and cultural specific expressions. It re-assesses the notion of translation universals and translation literality, elaborates on the definition of translation units and syntactic equivalence, and investigates the impact of translation ambiguity and translation entropy. The results and findings are interpreted in the context of psycho-linguistic models of bilingualism and re-frame empirical translation process research within the context of modern dynamic cognitive theories of the mind. The volume bridges the gap between translation process research and machine translation research. It appeals to students and researchers in the fields.

Diversity, Freedom and Evolution

William Magnusson
Diversity Freedom and Evolution Book PDF

Author : William Magnusson
Publisher : Cambridge Scholars Publishing
Page : 113 pages
File Size : 51,5 Mb
Release : 2019-03-22
Category : Science
ISBN : 9781527531871

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Diversity, Freedom and Evolution by William Magnusson Pdf

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 and moral values that people cherish, whatever their beliefs. Those values can apply to everything that has evolved or will evolve, whether they are humans, other organisms, machines or memes. There is potential for all people who believe in the power of evolution, whether they link that to other spiritual beliefs or not, to unite in a congregation of evolutionists. This will not only help reduce present-day conflicts; it will also be important in the future when we have to face other challenges, such as machine self-awareness. Evolution has made humans not only self-aware, but aware of the universe. As they are a part of the universe, that means that the universe is self-aware in the same sense as any other entity is self-aware, and this gives enormous potential to change the future that mainline physicists tell us will be dark and dead.

The New Statistics with R

Andy Hector
The New Statistics with R Book PDF

Author : Andy Hector
Publisher : Oxford University Press
Page : 277 pages
File Size : 44,8 Mb
Release : 2021
Category : Mathematics
ISBN : 9780198798170

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The New Statistics with R by Andy Hector Pdf

Statistical methods are a key tool for all scientists working with data, but learning the basics continues to challenge successive generations of students. This accessible textbook provides an up-to-date introduction to the classical techniques and modern extensions of linear model analysis-one of the most useful approaches for investigating scientific data in the life and environmental sciences. While some of the foundational analyses (e.g. t tests, regression, ANOVA) are as useful now as ever, best practice moves on and there are many new general developments that offer great potential. The book emphasizes an estimation-based approach that takes account of recent criticisms of over-use of probability values and introduces the alternative approach that uses information criteria. This new edition includes the latest advances in R and related software and has been thoroughly "road-tested" over the last decade to create a proven textbook that teaches linear and generalized linear model analysis to students of ecology, evolution, and environmental studies (including worked analyses of data sets relevant to all three disciplines). While R is used throughout, the focus remains firmly on statistical analysis. The New Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners in the fields of ecology, evolution and environmental studies.

Prediction and Causality in Econometrics and Related Topics

Nguyen Ngoc Thach,Doan Thanh Ha,Nguyen Duc Trung,Vladik Kreinovich
Prediction and Causality in Econometrics and Related Topics Book PDF

Author : Nguyen Ngoc Thach,Doan Thanh Ha,Nguyen Duc Trung,Vladik Kreinovich
Publisher : Springer Nature
Page : 691 pages
File Size : 51,5 Mb
Release : 2021-07-26
Category : Technology & Engineering
ISBN : 9783030770945

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Prediction and Causality in Econometrics and Related Topics by Nguyen Ngoc Thach,Doan Thanh Ha,Nguyen Duc Trung,Vladik Kreinovich Pdf

This book provides the ultimate goal of economic studies to predict how the economy develops—and what will happen if we implement different policies. To be able to do that, we need to have a good understanding of what causes what in economics. Prediction and causality in economics are the main topics of this book's chapters; they use both more traditional and more innovative techniques—including quantum ideas -- to make predictions about the world economy (international trade, exchange rates), about a country's economy (gross domestic product, stock index, inflation rate), and about individual enterprises, banks, and micro-finance institutions: their future performance (including the risk of bankruptcy), their stock prices, and their liquidity. Several papers study how COVID-19 has influenced the world economy. This book helps practitioners and researchers to learn more about prediction and causality in economics -- and to further develop this important research direction.