Jennifer A. Hoeting – författare

This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.

This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing.  The book is comprised of four main parts spanning the field: OptimizationIntegration and SimulationBootstrappingDensity Estimation and SmoothingWithin these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods.  The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data.  The book website now includes comprehensive R code for the entire book.  There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing.  The book is comprised of four main parts spanning the field:

Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing

Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods.  The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data.  The book website now includes comprehensive R code for the entire book.  There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

This new edition continues to serve as a comprehensive guide to modern and classical methods of statistical computing.  The book is comprised of four main parts spanning the field:

Optimization Integration and Simulation Bootstrapping Density Estimation and Smoothing

Within these sections,each chapter includes a comprehensive introduction and step-by-step implementation summaries to accompany the explanations of key methods.  The new edition includes updated coverage and existing topics as well as new topics such as adaptive MCMC and bootstrapping for correlated data.  The book website now includes comprehensive R code for the entire book.  There are extensive exercises, real examples, and helpful insights about how to use the methods in practice.

This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface.

Features:

An internationally regarded editorial team.

A distinguished collection of contributors.

A thoroughly contemporary treatment of a substantial interdisciplinary interface.

Written to engage both statisticians as well as quantitative environmental researchers.

34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.

This handbook focuses on the enormous literature applying statistical methodology and modelling to environmental and ecological processes. The 21st century statistics community has become increasingly interdisciplinary, bringing a large collection of modern tools to all areas of application in environmental processes. In addition, the environmental community has substantially increased its scope of data collection including observational data, satellite-derived data, and computer model output. The resultant impact in this latter community has been substantial; no longer are simple regression and analysis of variance methods adequate. The contribution of this handbook is to assemble a state-of-the-art view of this interface. Features: An internationally regarded editorial team. A distinguished collection of contributors. A thoroughly contemporary treatment of a substantial interdisciplinary interface. Written to engage both statisticians as well as quantitative environmental researchers. 34 chapters covering methodology, ecological processes, environmental exposure, and statistical methods in climate science.