3 papers
math.ST2021
Stationarity and inference in multistate promoter models of stochastic gene expression via stick-breaking measures
William Lippitt, Sunder Sethuraman, Xueying Tang
In a general stochastic multistate promoter model of dynamic mRNA/protein interactions, we identify the stationary joint distribution of the promoter state, mRNA, and protein level…
math.ST2021
On the use of Markovian stick-breaking priors
William Lippitt, Sunder Sethuraman
In [10], a `Markovian stick-breaking' process which generalizes the Dirichlet process with respect to a discrete base space was introduced. In particular,…
math.PR2019
Stick-breaking processes, clumping, and Markov chain occupation laws
Zach Dietz, William Lippitt, Sunder Sethuraman
We consider the connections among `clumped' residual allocation models (RAMs), a general class of stick-breaking processes including Dirichlet processes, and the occupation laws of…