For each migration model parameterization (Additional file 1: Figure S2) and each tree (see Methods), stochastic mapping is used to sample the internal state of branches and the timing of migration events.
This mapping allows us to generate a stochastic realization of the state of branches along the tree, in addition to the state of internal nodes, and in so doing, provides samples of migration and mutation events, and their timing along the tree that lead to the observed tip states.
The state of each branch is governed by the variables p ik(s), which is the probability that branch i is in state k at time s in the past.
The state of every branch should be equal or less than 1: s_{ij} = s_{ij}^{text{d}} + s_{ji}^{text{r}} le 1 (20).
The binary variable (s_{ij} (i < j)) represents the open or closed state of every branch, where 1 denotes closed and 0 denotes open.
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It creates a stable/* branch from the current state of the master branch and introduces any new release-critical fix discovered until the release day.
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Following a coalescent event, the state of the new branch α depends on the state of the daughter lineage i or j when it reproduced.
