#55 Phylogenetics and the likelihood gradient with Xiang Ji
Update: 2021-01-13
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
If you enjoyed this episode, please consider supporting the podcast on Patreon.
Comments
Top Podcasts
The Best New Comedy Podcast Right Now – June 2024The Best News Podcast Right Now – June 2024The Best New Business Podcast Right Now – June 2024The Best New Sports Podcast Right Now – June 2024The Best New True Crime Podcast Right Now – June 2024The Best New Joe Rogan Experience Podcast Right Now – June 20The Best New Dan Bongino Show Podcast Right Now – June 20The Best New Mark Levin Podcast – June 2024
In Channel