67 citations · 134 across the 14 of their papers we have counts for
4 papers · 1 filter
Statistical Disaggregation -- a Monte Carlo Approach for Imputation under Constraints
Shenggang Hu, Hongsheng Dai, Fanlin Meng +3
Equality-constrained models naturally arise in problems in which measurements are taken at different levels of resolution. The challenge in this setting is that the models usually…
Sampling using Adaptive Regenerative Processes
Hector McKimm, Andi Q Wang, Murray Pollock +2
Enriching Brownian motion with regenerations from a fixed regeneration distribution at a particular regeneration rate results in a Markov process that has a target distribu…
The computational cost of blocking for sampling discretely observed diffusions
Marcin Mider, Paul A. Jenkins, Murray Pollock +1
Many approaches for conducting Bayesian inference on discretely observed diffusions involve imputing diffusion bridges between observations. This can be computationally challenging…
Piecewise Deterministic Markov Processes for Continuous-Time Monte Carlo
Paul Fearnhead, Joris Bierkens, Murray Pollock +1
Recently there have been exciting developments in Monte Carlo methods, with the development of new MCMC and sequential Monte Carlo (SMC) algorithms which are based on continuous-ti…