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The likelihood was calculated using the pruning algorithm of Felsenstein.
For reversible substitution processes, the probability of the sequence alignment given the tree can be efficiently evaluated using the pruning algorithm (Felsenstein, 1981).
To compute Equation (10), we numerically approximate the integral using the rectangle method with the midpoint rule, computing each of the probabilities using the pruning algorithm.
Given a matrix Q we can calculate the probability of a site of our alignment, Pr(a i | T i, b T i ) using the Pruning algorithm of Felsenstein (1981).
Letting Loss be a Boolean variable indicating whether such an event occurs, we can rewrite the probability as (9) The first term in the sum in Equation (9) is the probability of no loss event [1− F(D), Equation (7)] times the probability under the no-loss model, which can be computed using the pruning algorithm.
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Simulation results demonstrate the advantage of nonmyopic scheduling over myopic scheduling and the significant savings in computational and memory resources when using the pruning algorithms.
Using the pruning technology can reduce the search space to a certain extent, and thus improve the efficiency of the algorithm.
Using the pruning shears, trim off any unwanted vine tendrils.
Therefore, the pruning algorithm is used.
In other cases, changes to the basis network to be pruned, or to the pruning algorithm, can mitigate the problem.
This fools the pruning algorithm to believe the network is fully connected and no retransmissions needed.
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