Piecewise deterministic Markov processes for scalable Monte Carlo on restricted domains


One of the main technical challenges associated with likelihood-based inference for big data is the fact that likelihood calculation is computationally expensive (typically O ( N ) for data sets of size N ). MCMC methods built from piecewise deterministic Markov processes (PDMPs) offer …

Stat. Probab. Lett.