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Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and Stan

Bayesian Data Analysis in Ecology Using Linear Models with R, BUGS, and STAN examines the Bayesian and frequentist methods;

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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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Dynamic Linear Models with R

series analysis is required, although familiarity with basic statistics and R is assumed.;

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Data Analysis Using Hierarchical Generalized Linear Models with R

within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to;

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Data Analysis Using Hierarchical Generalized Linear Models with R

within the field and, using data examples, illustrates how to analyse various kinds of data using R. It provides a likelihood approach to;

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Extending The Linear Model With R

expanded both in popularity and in the number of packages available. Extending the Linear Model with R: Generalized Linear, Mixed Effects and;

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Time Series Analysis for the State Space Model with R Stan

practical exercise using RStan based on real data promotes understanding and enhances the reader's analytical capability.;

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Time Series Analysis for the State Space Model with R Stan

practical exercise using RStan based on real data promotes understanding and enhances the reader's analytical capability.;

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Bayesian Models for Astrophysical Data

This comprehensive guide to Bayesian methods in astronomy enables hands-on work by supplying complete R, JAGS, Python, and Stan code, to;

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Bayesian Analysis for Population Ecology

averaging, Bayesian Analysis for Population Ecology presents up-to-date methods for analysing complex ecological data. Leaders in the statistical;

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Bayesian Analysis for Population Ecology

, Bayesian Analysis for Population Ecology presents up-to-date methods for analysing complex ecological data. Leaders in the statistical ecology;

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Doing Bayesian Data Analysis

Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan, Second Edition provides an accessible approach for conducting Bayesian;

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An Introduction to Generalized Linear Models

framework for statistical modeling. This new edition of a bestseller has been updated with Stata, R, and WinBUGS code as well as three new chapters;

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Learning Bayesian Models with R: Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems

Become an expert in Bayesian Machine Learning methods using R and apply them to solve real-world big data problems About This Book;

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Bayesian Statistical Methods

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis;

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Bayesian Statistical Methods

Bayesian Statistical Methods provides data scientists with the foundational and computational tools needed to carry out a Bayesian analysis;

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Bayesian Analysis with Python

Bayesian modeling with PyMC3 and exploratory analysis of Bayesian models with ArviZ Key Features A step-by-step guide to conduct Bayesian;

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Doing Bayesian Data Analysis

Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first;

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R for Marketing Research and Analytics

modeling, market basket analysis, structural equation modeling, and conjoint analysis in R. The text uniquely presents Bayesian models with a;

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Bayesian Analysis with Python

Students, researchers and data scientists who wish to learn Bayesian data analysis with Python and implement probabilistic models in their day to;

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Bringing Bayesian Models to Life

. Features: R code implementing algorithms to fit Bayesian models using real and simulated data examples. A comprehensive review;

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Bringing Bayesian Models to Life

. Features: R code implementing algorithms to fit Bayesian models using real and simulated data examples. A comprehensive;

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Advanced R Statistical Programming and Data Models

data visualization, linear and advanced regression, additive models, survival / time to event analysis Handle machine learning using R;

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Statistical Rethinking

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds your knowledge of and confidence in making inferences from;

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Bayesian Methods for Ecology

The interest in using Bayesian methods in ecology is increasing, however many ecologists have difficulty with conducting the required;

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An Introduction to Generalized Linear Models

nominal and ordinal regression, survival analysis, non-linear associations and longitudinal analysis Connects Bayesian analysis and MCMC;

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An Introduction to Generalized Linear Models

nominal and ordinal regression, survival analysis, non-linear associations and longitudinal analysis Connects Bayesian analysis and MCMC;

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