2 papers
stat.ME2026
Spectral divide-and-conquer MCMC for long stationary time series
Zixuan Wang, Matias Quiroz, Feng Li +2
The temporal dependence inherent in time series models poses a fundamental challenge for distributed Bayesian inference, as it precludes embarrassingly parallel algorithms based on…
stat.CO2026
Spectral subsampling MCMC for Lévy-driven continuous-time ARMA models with expensive likelihood contributions
Thomas Goodwin, Matias Quiroz, Robert Kohn +1
Subsampling-based Markov chain Monte Carlo (MCMC) algorithms aim to accelerate Bayesian inference by evaluating the likelihood using only a subset of the data at each iteration. Ho…