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Environmental And Ecological Statistics With R Second Edition

Author: Song S. Qian
Publisher: CRC Press
ISBN: 1498728758
Size: 55.69 MB
Format: PDF
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Emphasizing the inductive nature of statistical thinking, Environmental and Ecological Statistics with R, Second Edition, connects applied statistics to the environmental and ecological fields. Using examples from published works in the ecological and environmental literature, the book explains the approach to solving a statistical problem, covering model specification, parameter estimation, and model evaluation. It includes many examples to illustrate the statistical methods and presents R code for their implementation. The emphasis is on model interpretation and assessment, and using several core examples throughout the book, the author illustrates the iterative nature of statistical inference. The book starts with a description of commonly used statistical assumptions and exploratory data analysis tools for the verification of these assumptions. It then focuses on the process of building suitable statistical models, including linear and nonlinear models, classification and regression trees, generalized linear models, and multilevel models. It also discusses the use of simulation for model checking, and provides tools for a critical assessment of the developed models. The second edition also includes a complete critique of a threshold model. Environmental and Ecological Statistics with R, Second Edition focuses on statistical modeling and data analysis for environmental and ecological problems. By guiding readers through the process of scientific problem solving and statistical model development, it eases the transition from scientific hypothesis to statistical model.

Introduction To Hierarchical Bayesian Modeling For Ecological Data

Author: Eric Parent
Publisher: CRC Press
ISBN: 1584889195
Size: 27.80 MB
Format: PDF, Mobi
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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 present the concepts and techniques of the Bayesian paradigm from a practical point of view using real case studies. They emphasize how hierarchical Bayesian modeling supports multidimensional models involving complex interactions between parameters and latent variables. Data sets, exercises, and R and WinBUGS codes are available on the authors’ website. This book shows how Bayesian statistical modeling provides an intuitive way to organize data, test ideas, investigate competing hypotheses, and assess degrees of confidence of predictions. It also illustrates how conditional reasoning can dismantle a complex reality into more understandable pieces. As conditional reasoning is intimately linked with Bayesian thinking, considering hierarchical models within the Bayesian setting offers a unified and coherent framework for modeling, estimation, and prediction.

Handbook Of Spatial Point Pattern Analysis In Ecology

Author: Thorsten Wiegand
Publisher: CRC Press
ISBN: 142008254X
Size: 12.30 MB
Format: PDF
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Understand How to Analyze and Interpret Information in Ecological Point Patterns Although numerous statistical methods for analyzing spatial point patterns have been available for several decades, they haven’t been extensively applied in an ecological context. Addressing this gap, Handbook of Spatial Point-Pattern Analysis in Ecology shows how the techniques of point-pattern analysis are useful for tackling ecological problems. Within an ecological framework, the book guides readers through a variety of methods for different data types and aids in the interpretation of the results obtained by point-pattern analysis. Ideal for empirical ecologists who want to avoid advanced theoretical literature, the book covers statistical techniques for analyzing and interpreting the information contained in ecological patterns. It presents methods used to extract information hidden in spatial point-pattern data that may point to the underlying processes. The authors focus on point processes and null models that have proven their immediate utility for broad ecological applications, such as cluster processes. Along with the techniques, the handbook provides a comprehensive selection of real-world examples. Most of the examples are analyzed using Programita, a continuously updated software package based on the authors’ many years of teaching and collaborative research in ecological point-pattern analysis. Programita is tailored to meet the needs of real-world applications in ecology. The software and a manual are available online.

Environmental Statistics With S Plus

Author: Steven P. Millard
Publisher: CRC Press
ISBN: 142003717X
Size: 30.92 MB
Format: PDF, ePub
View: 1990
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A clear, comprehensive treatment of the subject, Environmental Statistics with S-PLUS surveys the vast array of statistical methods used to collect and analyze environmental data. The book explains what these methods are, how to use them, and where to find references to them. In addition, it provides insight into what to think about before you collect environmental data, how to collect the data, and how to make sense of it after collection. A unique and powerful feature of the book is its integration with the commercially available software package S-Plus and the add-on modules EnvironmentalStats for S-PLUS, S+SpatialStats, and S-PLUS for ArcView. The book presents data sets to explain statistical methods, and then shows how to implement these methods by providing the commands for and the results from the software. This survey of statistical methods, definitions, and concepts helps you collect and effectively analyze data for environmental pollution problems. Using the S-PLUS software in conjunction with this text will no doubt increase understanding of the methods.

Introduction To Ecological Sampling

Author: Bryan F.J. Manly
Publisher: CRC Press
ISBN: 1466555149
Size: 32.37 MB
Format: PDF, ePub, Docs
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An Easy-to-Understand Treatment of Ecological Sampling Methods and Data Analysis Including only the necessary mathematical derivations, Introduction to Ecological Sampling shows how to use sampling procedures for ecological and environmental studies. It incorporates both traditional sampling methods and recent developments in environmental and ecological sampling methods. After an introduction, the book presents standard sampling methods and analyses. Subsequent chapters delve into specialized topics written by well-known researchers. These chapters cover adaptive sampling methods, line transect sampling, removal and change-in-ratio methods, plotless sampling, mark-recapture sampling of closed and open populations, occupancy models, sampling designs for environmental modeling, and trend analysis. The book explains the methods as simply as possible, keeping equations and their derivations to a minimum. It provides references to important, more advanced sampling methods and analyses. It also directs readers to computer programs that can be used to perform the analyses. Accessible to biologists, the text only assumes a basic knowledge of statistical methods. It is suitable for an introductory course on methods for collecting and analyzing ecological and environmental data.

Statistical Methods For Field And Laboratory Studies In Behavioral Ecology

Author: Scott Pardo
Publisher: CRC Press
ISBN: 1351723162
Size: 20.50 MB
Format: PDF, Kindle
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Statistical Methods for Field and Laboratory Studies in Behavioral Ecology focuses on how statistical methods may be used to make sense of behavioral ecology and other data. It presents fundamental concepts in statistical inference and intermediate topics such as multiple least squares regression and ANOVA. The objective is to teach students to recognize situations where various statistical methods should be used, understand the strengths and limitations of the methods, and to show how they are implemented in R code. Examples are based on research described in the literature of behavioral ecology, with data sets and analysis code provided. Features: This intermediate to advanced statistical methods text was written with the behavioral ecologist in mind Computer programs are provided, written in the R language. Datasets are also provided, mostly based, at least to some degree, on real studies. Methods and ideas discussed include multiple regression and ANOVA, logistic and Poisson regression, machine learning and model identification, time-to-event modeling, time series and stochastic modeling, game-theoretic modeling, multivariate methods, study design/sample size, and what to do when things go wrong. It is assumed that the reader has already had exposure to statistics through a first introductory course at least, and also has sufficient knowledge of R. However, some introductory material is included to aid the less initiated reader. Scott Pardo, Ph.D., is an accredited professional statistician (PStat®) by the American Statistical Association. Michael Pardo is a Ph.D. is a candidate in behavioral ecology at Cornell University, specializing in animal communication and social behavior. ? ?

Handbook Of Spatial Statistics

Author: Alan E. Gelfand
Publisher: CRC Press
ISBN: 9781420072884
Size: 57.21 MB
Format: PDF, Docs
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Assembling a collection of very prominent researchers in the field, the Handbook of Spatial Statistics presents a comprehensive treatment of both classical and state-of-the-art aspects of this maturing area. It takes a unified, integrated approach to the material, providing cross-references among chapters. The handbook begins with a historical introduction detailing the evolution of the field. It then focuses on the three main branches of spatial statistics: continuous spatial variation (point referenced data); discrete spatial variation, including lattice and areal unit data; and spatial point patterns. The book also contains a section on space–time work as well as a section on important topics that build upon earlier chapters. By collecting the major work in the field in one source, along with including an extensive bibliography, this handbook will assist future research efforts. It deftly balances theory and application, strongly emphasizes modeling, and introduces many real data analysis examples.

Environmental Statistics With R And S Plus Second Edition

Author: Steven P. Millard
Publisher: CRC PressI Llc
ISBN: 9781439810279
Size: 34.48 MB
Format: PDF, Mobi
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Condensed and reorganized, this comprehensive second edition covers most of the statistical methods used in the field and now features the use of both R and S-Plus software. Continuing to emphasize lognormal distributions, censored data, and computing, this edition includes additional material on equivalence testing. It also illustrates environmental sampling designs using the public domain package VSP. In addition, the authors provide a detailed discussion of spatial mapping procedures and spatial mapping analysis in R. Along with updated problem sets and new examples, this edition contains numerous new references that bring the research up to date.

Structural Analysis Of Polymeric Composite Materials Second Edition

Author: Mark E. Tuttle
Publisher: CRC Press
ISBN: 143987512X
Size: 34.95 MB
Format: PDF, ePub, Docs
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Structural Analysis of Polymeric Composite Materials, Second Edition introduces the mechanics of composite materials and structures and combines classical lamination theory with macromechanical failure principles for prediction and optimization of composite structural performance. It addresses topics such as high-strength fibers, manufacturing techniques, commercially available compounds, and the behavior of anisotropic, orthotropic, and transversely isotropic materials and structures subjected to complex loading. Emphasizing the macromechanical (structural) level over micromechanical issues and analyses, this unique book integrates effects of environment at the outset to establish a coherent and updated knowledge base. In addition, each chapter includes example problems to illustrate the concepts presented.

Bayesian Analysis For Population Ecology

Author: Ruth King
Publisher: CRC Press
ISBN: 9781439811887
Size: 13.95 MB
Format: PDF, Docs
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Novel Statistical Tools for Conserving and Managing Populations By 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 models, evaluate posterior model probabilities, and deal with missing data, modern Bayesian methods have become important in this area of statistical inference and forecasting. Emphasising model choice and model averaging, Bayesian Analysis for Population Ecology presents up-to-date methods for analysing complex ecological data. Leaders in the statistical ecology field, the authors apply the theory to a wide range of actual case studies and illustrate the methods using WinBUGS and R. The computer programs and full details of the data sets are available on the book’s website. The first part of the book focuses on models and their corresponding likelihood functions. The authors examine classical methods of inference for estimating model parameters, including maximum-likelihood estimates of parameters using numerical optimisation algorithms. After building this foundation, the authors develop the Bayesian approach for fitting models to data. They also compare Bayesian and traditional approaches to model fitting and inference. Exploring challenging problems in population ecology, this book shows how to use the latest Bayesian methods to analyse data. It enables readers to apply the methods to their own problems with confidence.