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Introduction to Hierarchical Bayesian Modeling for Ecological Data

by Eric Parent, Etienne Rivot ...

Series series Chapman & Hall/CRC Applied Environmental Statistics
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 statisti ... Read more

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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 statisti
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A Student’s Guide to Bayesian Statistics

by Ben Lambert ...

Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics.Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at ... Read more

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Supported by a wealth of learning features, exercises, and visual elements as well as online video tutorials and interactive simulations, this book is the first student-focused introduction to Bayesian statistics.Without sacrificing technical integrity for the sake of simplicity, the author draws upon accessible, student-friendly language to provide approachable instruction perfectly aimed at
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Statistical Rethinking

A Bayesian Course with Examples in R and STAN

by Richard McElreath ...

Series series Chapman & Hall/CRC Texts in Statistical Science
Winner of the 2023 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This ... Read more

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Winner of the 2023 De Groot Prize awarded by the International Society for Bayesian Analysis (ISBA)Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from data. Reflecting the need for scripting in today's model-based statistics, the book pushes you to perform step-by-step calculations that are usually automated. This
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Ecological Models and Data in R

by Benjamin M. Bolker ...

Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive ... Read more

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Ecological Models and Data in R is the first truly practical introduction to modern statistical methods for ecology. In step-by-step detail, the book teaches ecology graduate students and researchers everything they need to know in order to use maximum likelihood, information-theoretic, and Bayesian techniques to analyze their own data using the programming language R. Drawing on extensive
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Bayesian Statistics

An Introduction

by Peter M. Lee ...

Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.This new fourth edition looks at recent techniques such as variational methods, Bayesian importance ... Read more

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Bayesian Statistics is the school of thought that combines prior beliefs with the likelihood of a hypothesis to arrive at posterior beliefs. The first edition of Peter Lee’s book appeared in 1989, but the subject has moved ever onwards, with increasing emphasis on Monte Carlo based techniques.This new fourth edition looks at recent techniques such as variational methods, Bayesian importance
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Generalized Additive Models

An Introduction with R, Second Edition

by Simon N. Wood ...

Series series Chapman & Hall/CRC Texts in Statistical Science
The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before ... Read more

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The first edition of this book has established itself as one of the leading references on generalized additive models (GAMs), and the only book on the topic to be introductory in nature with a wealth of practical examples and software implementation. It is self-contained, providing the necessary background in linear models, linear mixed models, and generalized linear models (GLMs), before
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How to be a Quantitative Ecologist

The 'A to R' of Green Mathematics and Statistics

by Jason Matthiopoulos ...

How to be a Quantitative Ecologist: The 'A to R' of Green Mathematics and StatisticsEcological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This textbook provides a practical introduction to quantitative ecology for students and practitioners who have ... Read more

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How to be a Quantitative Ecologist: The 'A to R' of Green Mathematics and StatisticsEcological research is becoming increasingly quantitative, yet students often opt out of courses in mathematics and statistics, unwittingly limiting their ability to carry out research in the future. This textbook provides a practical introduction to quantitative ecology for students and practitioners who have
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Introduction to Bayesian Econometrics

by Edward Greenberg ...

This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior ... Read more

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This textbook explains the basic ideas of subjective probability and shows how subjective probabilities must obey the usual rules of probability to ensure coherency. It defines the likelihood function, prior distributions and posterior distributions. It explains how posterior distributions are the basis for inference and explores their basic properties. Various methods of specifying prior
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Hidden Markov Models for Time Series

An Introduction Using R, Second Edition

by Walter Zucchini, Iain L. MacDonald, Roland Langrock ...

Series series Chapman & Hall/CRC Monographs on Statistics and Applied Probability
Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses.After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian ... Read more

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Hidden Markov Models for Time Series: An Introduction Using R, Second Edition illustrates the great flexibility of hidden Markov models (HMMs) as general-purpose models for time series data. The book provides a broad understanding of the models and their uses.After presenting the basic model formulation, the book covers estimation, forecasting, decoding, prediction, model selection, and Bayesian
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Bayesian Population Analysis using WinBUGS

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by Michael Schaub, Marc Kéry ...

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 ... Read more

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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
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Spatial Statistics and Geostatistics

Theory and Applications for Geographic Information Science and Technology

by Yongwan Chun, Daniel A. Griffith ...

Series series SAGE Advances in Geographic Information Science and Technology Series
"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice"- Professor Tao Cheng, University College LondonFocusing specifically on spatial statistics and including components for ArcGIS, R, SAS ... Read more

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"Ideal for anyone who wishes to gain a practical understanding of spatial statistics and geostatistics. Difficult concepts are well explained and supported by excellent examples in R code, allowing readers to see how each of the methods is implemented in practice"- Professor Tao Cheng, University College LondonFocusing specifically on spatial statistics and including components for ArcGIS, R, SAS
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Quantitative Analysis in Archaeology

by Todd L. VanPool, Robert D. Leonard ...

Quantitative Analysis in Archaeology introduces the application of quantitative methods in archaeology. It outlines conceptual and statistical principles, illustrates their application, and provides problem sets for practice.Discusses both methodological frameworks and quantitative methods of archaeological analysisPresents statistical material in a clear and straightforward manner ideal for ... Read more

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Quantitative Analysis in Archaeology introduces the application of quantitative methods in archaeology. It outlines conceptual and statistical principles, illustrates their application, and provides problem sets for practice.Discusses both methodological frameworks and quantitative methods of archaeological analysisPresents statistical material in a clear and straightforward manner ideal for
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A Student’s Guide to Bayesian Statistics

Statistical Rethinking

Ecological Models and Data in R

Bayesian Statistics

Generalized Additive Models

How to be a Quantitative Ecologist

Introduction to Bayesian Econometrics

Hidden Markov Models for Time Series

Bayesian Population Analysis using WinBUGS

Spatial Statistics and Geostatistics

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