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Hierarchical Modeling and Inference in Ecology

.This book describes a general and flexible framework for modeling and inference in ecological systems based on hierarchical models;

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

class of models. Applied Hierarchical Modeling in Ecology, Volume 1serves as an indispensable manual for practicing field biologists, and as a;

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Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS

Applied Hierarchical Modeling in Ecology: Analysis of Distribution, Abundance and Species Richness in R and BUGS, Volume Two: Dynamic and;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian;

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Introduction to Hierarchical Bayesian Modeling for Ecological Data

Making statistical modeling and inference more accessible to ecologists and related scientists, Introduction to Hierarchical Bayesian;

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Probability and Bayesian Modeling

, Bayesian inference is described for hierarchical and regression models including logistic regression. The book presents several case studies;

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Bayesian Disease Mapping

Focusing on data commonly found in public health databases and clinical settings, Bayesian Disease Mapping: Hierarchical Modeling;

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Bayesian Modeling Using WinBUGS

implementation of key principles. The book begins with a basic introduction to Bayesian inference and the WinBUGS software and goes on to cover key;

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Models Of The Ecological Hierarchy

In the application of statistics to ecological inference problems, hierarchical models combine explicit models of ecological system;

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Bayesian Models

, hierarchical models, Markov chain Monte Carlo, and inference from single and multiple models. This unique book places less emphasis on computer coding;

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BAYESIAN INFERENCE

and outliers; hierarchical, multivariate and non-parametric models; asymptotics; computations and Monte Carlo methods; and Bayesian;

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Dynamic Econometric Modeling

modeling, nonlinear structural modeling, time series modeling, nonparametric inference, and chaotic attractor inference. The contents of this;

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Statistical Methods for Field and Laboratory Studies in Behavioral Ecology

Statistical Methods for Field and Laboratory Studies in Behavioral Ecology focuses on how statistical methods may be used to make sense;

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Statistical Methods for Field and Laboratory Studies in Behavioral Ecology

Statistical Methods for Field and Laboratory Studies in Behavioral Ecology focuses on how statistical methods may be used to make sense;

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International Symposia in Economic Theory and Econometrics

modeling, nonlinear structural modeling, time series modeling, nonparametric inference, and chaotic attractor inference. The contents of this;

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International Symposia in Economic Theory and Econometrics

modeling, nonlinear structural modeling, time series modeling, nonparametric inference, and chaotic attractor inference. The contents of this;

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Computational Modeling of Cognition and Behavior

likelihood and Bayesian estimation, including fitting hierarchical and mixture models. Model comparison is described as a core philosophy;

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Computational Modeling of Cognition and Behavior

likelihood and Bayesian estimation, including fitting hierarchical and mixture models. Model comparison is described as a core philosophy;

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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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Bayesian Disease Mapping

Since the publication of the second edition, many new Bayesian tools and methods have been developed for space-time data analysis, the;

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Computational Ecology: Graphs, Networks And Agent-based Modeling

Graphs, networks and agent-based modeling are the most thriving and attracting sciences used in ecology and environmental sciences. As such;

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Core Statistics

methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.;

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Core Statistics

methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.;

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Hybrid Systems Biology

information including learning for biological systems, parametric synthesis and inference; stochastic and hybrid models in biology; hierarchical;

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Encyclopedia Of Theoretical Ecology

provide an introduction to broad fields such as Applied Ecology, Behavioral Ecology, Computational Ecology, Ecosystem Ecology, Epidemiology and;

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Mathematical Modeling in Microbial Ecology

of mathematical modeling in microbial ecology. The text presents a variety of systems, ranging from subcellular systems to ecosystems, and shows how to;

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Mathematical Modeling in Microbial Ecology

of mathematical modeling in microbial ecology. The text presents a variety of systems, ranging from subcellular systems to ecosystems, and shows how to;

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