Description

In this episode, we chat about phylogenetics with Xiang Ji. We start with a
general introduction to the field and then go deeper into the likelihood-based
methods (maximum likelihood and Bayesian inference). In particular, we talk
about the different ways to calculate the likelihood gradient, including a
linear-time exact gradient algorithm recently published by Xiang and his
colleagues.

Links:

• Gradients Do Grow on Trees: A Linear-Time O(N)-Dimensional Gradient for Statistical Phylogenetics
  (Xiang Ji, Zhenyu Zhang, Andrew Holbrook, Akihiko Nishimura, Guy Baele, Andrew Rambaut, Philippe Lemey, Marc A Suchard)
• BEAGLE: the package that implements the gradient algorithm
• BEAST: the program that implements the Hamiltonian Monte Carlo sampler and the molecular clock models

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