University of Arizona
Date & Time
September 16, 2022, 2:00 pm – 3:00 pm
Title: `Stick-breaking' measures: from time-inhomogeneous Markov chains to mRNA dynamics.
Abstract: In this talk, we begin with a notion of `Markovian stick-breaking' measures, a generalization of Dirichlet process priors used in Bayesian statistics. Then, we discuss curious connections between these measures and seemingly disparate objects such as empirical or `occupation' laws of certain time-inhomogeneous Markov chains, related to the Metropolis algorithm, and also the stationary distributions of multi-state promoter models of mRNA dynamics. Some synthetic data examples will also be presented. This work is with Zach Dietz, William Lippitt, and Xueying Tang.