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Bayesian Computation with R
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Abstract
Individual chapters are listed in the "Chapters" tab
Suggested Citation
DOI: 10.1007/978-0-387-92298-0
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Book Chapters
The following chapters of this book are listed in IDEAS- Jim Albert, 2009. "An Introduction to R," Springer Books, in: Bayesian Computation with R, chapter 1, pages 1-17, Springer.
- Jim Albert, 2009. "Introduction to Bayesian Thinking," Springer Books, in: Bayesian Computation with R, chapter 2, pages 19-37, Springer.
- Jim Albert, 2009. "Single-Parameter Models," Springer Books, in: Bayesian Computation with R, chapter 3, pages 39-61, Springer.
- Jim Albert, 2009. "Multiparameter Models," Springer Books, in: Bayesian Computation with R, chapter 4, pages 63-86, Springer.
- Jim Albert, 2009. "Introduction to Bayesian Computation," Springer Books, in: Bayesian Computation with R, chapter 5, pages 87-115, Springer.
- Jim Albert, 2009. "Markov Chain Monte Carlo Methods," Springer Books, in: Bayesian Computation with R, chapter 6, pages 117-152, Springer.
- Jim Albert, 2009. "Hierarchical Modeling," Springer Books, in: Bayesian Computation with R, chapter 7, pages 153-179, Springer.
- Jim Albert, 2009. "Model Comparison," Springer Books, in: Bayesian Computation with R, chapter 8, pages 181-204, Springer.
- Jim Albert, 2009. "Regression Models," Springer Books, in: Bayesian Computation with R, chapter 9, pages 205-234, Springer.
- Jim Albert, 2009. "Gibbs Sampling," Springer Books, in: Bayesian Computation with R, chapter 10, pages 235-264, Springer.
- Jim Albert, 2009. "Using R to Interface with WinBUGS," Springer Books, in: Bayesian Computation with R, chapter 11, pages 265-286, Springer.
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