PrioriTree is motivated by properties of the discrete-biogeographic models implemented in BEAST and issues with the commonly used default priors in BEAST, identified by Gao et al. (2022). PrioriTree allows users to specify priors on the discrete-biogeographic model parameters in a biologically informed way (e.g., specifying the prior on the average dispersal rate by expressing understanding on the expected number of pathogen dispersal events over the entire epidemic history). The program also allows users to specify these prior assumptions in an interactive manner; it dynamically visualizes the resulting prior distribution according to users' specification in real time. At the end, it generates a readily-runnable BEAST XML script (as well as the associated methods template) to perform the analysis that the user conceives. The other main functionality provided by PrioriTree is setting up additional analyses (including posterior-predictive checking, data cloning, and robust Bayesian) to evaluate the impact of alternative discrete-biogeographic (prior)model specification and visualizing the result.
Package details |
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Maintainer | Jiansi Gao <jsigao@gamil.com> |
License | GPL-3 |
Version | 0.0.1 |
Package repository | View on GitHub |
Installation |
Install the latest version of this package by entering the following in R:
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