ENVIRONMENTAL AND ECOLOGICAL STATISTICS WITH R CHAPMAN HALL CRC APPLIED ENVIRONMENTAL STATISTICS

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Environmental And Ecological Statistics With R Second Edition

Author : Song S. Qian
ISBN : 9781498728751
Genre : Mathematics
File Size : 37.95 MB
Format : PDF, Docs
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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.
Category: Mathematics

Environmental And Ecological Statistics With R

Author : Song S. Qian
ISBN : 9781498728737
Genre : Mathematics
File Size : 37.34 MB
Format : PDF, Mobi
Download : 884
Read : 547

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.
Category: Mathematics

Sampling Strategies For Natural Resources And The Environment

Author : Timothy G. Gregoire
ISBN : 9781584883708
Genre : Mathematics
File Size : 62.49 MB
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Written by renowned experts in the field, Sampling Strategies for Natural Resources and the Environment covers the sampling techniques used in ecology, forestry, environmental science, and natural resources. The book presents methods to estimate aggregate characteristics on a per unit area basis as well as on an elemental basis. In addition to common sampling designs such as simple random sampling and list sampling, the authors explore more specialized designs for sampling vegetation, including randomized branch sampling and 3P sampling. One of the book's unique features is the emphasis on areal sampling designs, including plot/quadrat sampling, Bitterlich sampling, line intersect sampling, and several lesser known designs. The book also provides comprehensive solutions to the problem of edge effect. Another distinguishing aspect is the inclusion of sampling designs for continuums, focusing on the methods of Monte Carlo integration. By presenting a conceptual understanding of each sampling design and estimation procedure as well as mathematical derivations and proofs in the chapter appendices, this text promotes a deep understanding of the underpinnings of sampling theory, estimation, and inference. Moreover, it will help you reliably sample natural populations and continuums.
Category: Mathematics

Introduction To Hierarchical Bayesian Modeling For Ecological Data

Author : Eric Parent
ISBN : 9781584889199
Genre : Mathematics
File Size : 89.7 MB
Format : PDF, ePub, Docs
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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.
Category: Mathematics

Statistical Geoinformatics For Human Environment Interface

Author : Wayne L. Myers
ISBN : 9781420082876
Genre : Mathematics
File Size : 47.58 MB
Format : PDF, Kindle
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Statistical Geoinformatics for Human Environment Interface presents two paradigms for studying both space and interface with regard to human/environment: localization and multiple indicators. The first approach localizes thematic targets by treating space as a pattern of vicinities, with the pattern being a square grid and the placement of vicinities centrically referenced. The second approach explores human/environment interface as an abstraction through indicators, neutralizing the common conundrum of how to reconcile disparate spatial structures such as points, lines, and polygons. These paired paradigms enable: The capacity to cope with complexity Systematic surveillance Visualization and communication Preliminary prioritization Coupling of GIS and statistical software Avenues for automation Illustrating the interdisciplinary nature of geoinformatics, this book offers a novel approach to the spatial analysis of human influences and environmental resources. It includes practical strategies for statistical and spatial analysis.
Category: Mathematics

Advances In Biometry

Author : Peter Armitage
ISBN : 0471160180
Genre : Medical
File Size : 24.39 MB
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Thirty leading international figures celebrate 50 years of achievement in biometry Over the past half-century, biometry has grown from a fledgling application of statistics to a vital and dynamic field that is relevant to some of the most important, substantive scientific and social issues that face us today. Statistical methodology has played a central role in the interpretation of experimental data in such dissimilar areas of biological and medical research as genetics, toxicology, neurology, and clinical trials. It has been applied in both the study and the solution of practical problems in the areas of public health, forestry, animal habitats, environmental contamination, and many more. In this book, 30 leading researchers--many of whom have made outstanding contributions to our understanding of the living world--discuss their specific branches of the subject and reflect on the exciting interaction of mathematics, statistics, and biology that has characterized the growth of biometry. Beginning with a brief history of the International Biometric Society and its journal Biometrics on the occasion of its 50th anniversary, the book goes on to offer a series of views on important developments in the field from two main perspectives: branches of statistical methodology that have played a central role in biometric applications, and branches of biology and medicine that have benefited from these applications. Selected topics are developed in depth, typically with a glance toward the future, and the book is extensively referenced throughout. Advances in Biometry is fascinating reading for students and researchers in applied statistics and mathematics, the biological and medical sciences, public health, and the environmental sciences.
Category: Medical

Statistical Methods For Field And Laboratory Studies In Behavioral Ecology

Author : Scott Pardo
ISBN : 9781351723169
Genre : Mathematics
File Size : 54.44 MB
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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.
Category: Mathematics

Spatial Conservation Prioritization

Author : Atte Moilanen
ISBN : STANFORD:36105124184628
Genre : Nature
File Size : 43.46 MB
Format : PDF
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In a coherent and comprehensive set of chapters, a team of leading scientists describe the present state-of-the-art in spatial conservation planning methodology with a focus on operational definitions and methods, supported by the latest technological details and applications of publicly available software.
Category: Nature