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First, we will use a vector scale move to propose changes to all branch rates simultaneously.This way we can sample the total branch rate independently of each individual rate, which can improve mixing.

In this model rates for each branch will be drawn independently from an exponential distribution. First, we’ll define the mean branch rate as an exponential random variable ( Then, use a for loop to define a rate for each branch., where each entry corresponds to a different branch in the tree, instead of a single rate that applies to all branches.Lastly, we will use two more specific moves to help improve MCMC convergence.The branch rates are independent and identically exponentially distributed with mean equal to the mean branch rate parameter we specified above.For each rate parameter we will also create scale proposal moves.

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