Phylogenetics and the likelihood gradient with Xiang Ji

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