2 papers
stat.AP2023
An SMC Algorithm on Distributed Memory with an Approx. Optimal L-Kernel
Conor Rosato, Alessandro Varsi, Joshua Murphy +1
Calibrating statistical models using Bayesian inference often requires both accurate and timely estimates of parameters of interest. Particle Markov Chain Monte Carlo (p-MCMC) and…
stat.AP2022
Inference of Stochastic Disease Transmission Models Using Particle-MCMC and a Gradient Based Proposal
Conor Rosato, John Harris, Jasmina Panovska-Griffiths +1
State-space models have been widely used to model the dynamics of communicable diseases in populations of interest by fitting to time-series data. Particle filters have enabled the…