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pro vyhledávání: '"Magee, P F"'
Autor:
Didier, Gustavo, Glatt-Holtz, Nathan E., Holbrook, Andrew J., Magee, Andrew F., Suchard, Marc A.
The continuous-time Markov chain (CTMC) is the mathematical workhorse of evolutionary biology. Learning CTMC model parameters using modern, gradient-based methods requires the derivative of the matrix exponential evaluated at the CTMC's infinitesimal
Externí odkaz:
http://arxiv.org/abs/2306.15841
Autor:
Magee, Andrew F., Holbrook, Andrew J., Pekar, Jonathan E., Caviedes-Solis, Itzue W., Matsen IV, Fredrick A., Baele, Guy, Wertheim, Joel O., Ji, Xiang, Lemey, Philippe, Suchard, Marc A.
Phylogenetic and discrete-trait evolutionary inference depend heavily on an appropriate characterization of the underlying character substitution process. In this paper, we present random-effects substitution models that extend common continuous-time
Externí odkaz:
http://arxiv.org/abs/2303.13642
Bayesian inference is a popular and widely-used approach to infer phylogenies (evolutionary trees). However, despite decades of widespread application, it remains difficult to judge how well a given Bayesian Markov chain Monte Carlo (MCMC) run explor
Externí odkaz:
http://arxiv.org/abs/2109.07629
Autor:
Fourment, Mathieu, Magee, Andrew F., Whidden, Chris, Bilge, Arman, Matsen IV, Frederick A., Minin, Vladimir N.
The marginal likelihood of a model is a key quantity for assessing the evidence provided by the data in support of a model. The marginal likelihood is the normalizing constant for the posterior density, obtained by integrating the product of the like
Externí odkaz:
http://arxiv.org/abs/1811.11804
Autor:
Whidden, Chris, Claywell, Brian C., Fisher, Thayer, Magee, Andrew F., Fourment, Mathieu, Matsen IV, Frederick A.
Bayesian Markov chain Monte Carlo explores tree space slowly, in part because it frequently returns to the same tree topology. An alternative strategy would be to explore tree space systematically, and never return to the same topology. In this paper
Externí odkaz:
http://arxiv.org/abs/1811.11007
Phylodynamics is an area of population genetics that uses genetic sequence data to estimate past population dynamics. Modern state-of-the-art Bayesian nonparametric methods for recovering population size trajectories of unknown form use either change
Externí odkaz:
http://arxiv.org/abs/1808.04401
Akademický článek
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Autor:
Schubel, Laura, Mete, Mihriye, Fong, Allan, Boxley, Christian, Barac, Ana, Gallagher, Christopher, Magee, Michelle F., Arem, Hannah
Publikováno v:
Journal of Ambulatory Care Management; Oct-Dec2024, Vol. 47 Issue 4, p228-238, 11p
Akademický článek
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The scientific enterprise depends critically on the preservation of and open access to published data. This basic tenet applies acutely to phylogenies (estimates of evolutionary relationships among species). Increasingly, phylogenies are estimated fr
Externí odkaz:
http://arxiv.org/abs/1405.6623