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Ajouter au panierTaschenbuch. Etat : Neu. Bayesian Phylogenetics | Methods, Algorithms, and Applications | Ming-Hui Chen (u. a.) | Taschenbuch | Einband - flex.(Paperback) | Englisch | 2022 | Chapman and Hall/CRC | EAN 9781032340234 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu.
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Ajouter au panierTaschenbuch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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 current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics. 396 pp. Englisch.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - High Quality Content by WIKIPEDIA articles! In biology, phenetics, also known as numerical taxonomy or taximetrics, is an attempt to classify organisms based on overall similarity, usually in morphology or other observable traits, regardless of their phylogeny or evolutionary relation.Phenetics has largely been superseded by cladistics for research into evolutionary relationships among species. However, certain phenetic methods, such as neighbor-joining, have found their way into cladistics, as a reasonable approximation of phylogeny when more advanced methods (such as Bayesian inference) are too computationally expensive.
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Ajouter au panierKartoniert / Broschiert. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.
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Ajouter au panierTaschenbuch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - 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 current trends in Bayesian phylogenetic research. Encouraging interdisciplinary research, this book introduces state-of-the-art phylogenetics to the Bayesian statistical community and, likewise, presents state-of-the-art Bayesian statistics to the phylogenetics community. The book emphasizes model selection, reflecting recent interest in accurately estimating marginal likelihoods. It also discusses new approaches to improve mixing in Bayesian phylogenetic analyses in which the tree topology varies. In addition, the book covers divergence time estimation, biologically realistic models, and the burgeoning interface between phylogenetics and population genetics.
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Ajouter au panierTaschenbuch. Etat : Neu. Phenetics | Biology, Phylogenetics, Cladistics, Neighbor-Joining, Bayesian Inference, Evolutionary Grade, Convergent Evolution, Folk Taxonomy, Taxonomy, DNA-DNA Hybridization | Lambert M. Surhone (u. a.) | Taschenbuch | Englisch | 2026 | OmniScriptum | EAN 9786130398033 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu Print on Demand.
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Ajouter au panierEtat : New. pp. 600 This item is printed on demand.
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Ajouter au panierGebunden. Etat : New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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.