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Bayesian computation with R
Overview of attention for book
Table of Contents
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Book Overview
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Chapter 1
An Introduction to R
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Chapter 2
Introduction to Bayesian Thinking
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Chapter 3
Single-Parameter Models
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Chapter 4
Multiparameter Models
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Chapter 5
Introduction to Bayesian Computation
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Chapter 6
Markov Chain Monte Carlo Methods
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Chapter 7
Hierarchical Modeling
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Chapter 8
Model Comparison
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Chapter 9
Regression Models
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Chapter 10
Gibbs Sampling
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Chapter 11
Using R to Interface with WinBUGS
Overall attention for this book and its chapters
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Mentioned by
syllabi
2
institutions with syllabi
Readers on
mendeley
11
Mendeley
Book overview
1. An Introduction to R
2. Introduction to Bayesian Thinking
3. Single-Parameter Models
4. Multiparameter Models
5. Introduction to Bayesian Computation
6. Markov Chain Monte Carlo Methods
7. Hierarchical Modeling
8. Model Comparison
9. Regression Models
10. Gibbs Sampling
11. Using R to Interface with WinBUGS
Summary
Syllabi
This data is correct as of December 2015 - for more up to date information, please visit
https://opensyllabus.org/
So far, Altmetric has seen this research output assigned in
2
syllabi from
2
institutions on Open Syllabus Project.
Institution
Syllabi count
Course subject areas covered
University of Plymouth
1
Unknown
Washington University in St Louis
1
Psychology