Bayesian Phylogenetics (PDF)
Methods, Algorithms, and Applications
(Sprache: Englisch)
Suitable for graduate-level researchers in statistics and biology, this book presents a snapshot of current trends in Bayesian phylogenetic research. It emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods....
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Suitable for graduate-level researchers in statistics and biology, this book presents a snapshot of current trends in Bayesian phylogenetic research. It emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. The book discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. It also covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.
Autoren-Porträt
Ming-Hui Chen is a professor of statistics and director of the Statistical Consulting Services at the University of Connecticut. He was the recipient of the 2013 American Association of the University Professors Research Excellence Award, the 2013 College of Liberal Arts and Sciences Excellence in Research Award in the Physical Sciences Division at the University of Connecticut, and the 2011 International Chinese Statisticians Association (ICSA) Outstanding Service Award. An elected fellow of the ASA and the IMS, Dr. Chen has served on numerous professional committees, including the 2013 president of the ICSA, the 2011-2013 board of directors of the International Society for Bayesian Analysis, the 2007-2010 executive director of the ICSA, and the 2004-2006 board of directors of the ICSA. He has also served on editorial boards of Bayesian Analysis, Journal of the American Statistical Association, Journal of Computational and Graphical Statistics, Lifetime Data Analysis, Sankhya, and Statistics and Its Interface. His research interests include Bayesian statistical methodology, Bayesian computation, Bayesian phylogenetics, categorical data analysis, design of Bayesian clinical trials, DNA microarray data analysis, meta-analysis, missing data analysis, Monte Carlo methodology, prior elicitation, statistical methodology and analysis for prostate cancer data, and survival data analysis.Lynn Kuo is a professor of statistics at the University of Connecticut. An elected fellow of the ASA, she was previously a research fellow in the Statistical Survey Institute at the USDA and at the Statistical and Applied Mathematical Sciences Institute (SAMSI). Dr. Kuo received an outstanding service award from ICSA in 2013 and was the secretary and treasurer of the Section of Bayesian Statistics of the ASA in 1998-1999. She has been an associate editor of the Journal of American Statistical
Bibliographische Angaben
- 2014, 1. Auflage, 396 Seiten, Englisch
- Herausgegeben: Ming-Hui Chen, Lynn Kuo, Paul O. Lewis
- Verlag: Taylor & Francis
- ISBN-10: 1466500824
- ISBN-13: 9781466500822
- Erscheinungsdatum: 27.05.2014
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