eBook - PDF
Bayesian Phylogenetics
Methods, Algorithms, and Applications
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- 396 pages
- English
- PDF
- Available on iOS & Android
eBook - PDF
Bayesian Phylogenetics
Methods, Algorithms, and Applications
Book details
Table of contents
Citations
About This Book
Offering a rich diversity of models, Bayesian phylogenetics allows evolutionary biologists, systematists, ecologists, and epidemiologists to obtain answers to very detailed phylogenetic questions. Suitable for graduate-level researchers in statistics and biology, Bayesian Phylogenetics: Methods, Algorithms, and Applications presents a snapshot of c
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Yes, you can access Bayesian Phylogenetics by Ming-Hui Chen, Lynn Kuo, Paul O. Lewis, Ming-Hui Chen, Lynn Kuo, Paul O. Lewis in PDF and/or ePUB format, as well as other popular books in Mathematics & Probability & Statistics. We have over one million books available in our catalogue for you to explore.
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Table of contents
- Front Cover
- Contents
- List of Figures
- List of Tables
- Preface
- Editors
- Contributors
- Chapter 1: Bayesian phylogenetics: methods, computational algorithms, and applications
- Chapter 2: Priors in Bayesian phylogenetics
- Chapter 3: Inated density ratio (IDR) method for estimating marginal likelihoods in Bayesian phylogenetics
- Chapter 4: Bayesian model selection in phylogenetics and genealogy-based population genetics
- Chapter 5: Variable tree topology stepping-stone marginal likelihood estimation
- Chapter 6: Consistency of marginal likelihood estimation when topology varies
- Chapter 7: Bayesian phylogeny analysis
- Chapter 8: SMC (sequential Monte Carlo) for Bayesian phylogenetics
- Chapter 9: Population model comparison using multi-locus datasets
- Chapter 10: Bayesian methods in the presence of recombination
- Chapter 11: Bayesian nonparametric phylodynamics
- Chapter 12: Sampling and summary statistics of endpoint-conditioned paths in DNA sequence evolution
- Chapter 13: Bayesian inference of species divergence times
- Bibliography
- Back Cover