834 citations · 3.9k across the 95 of their papers we have counts for
110 papers
Insufficient Gibbs Sampling
Antoine Luciano, Christian P. Robert, Robin J. Ryder
In some applied scenarios, the availability of complete data is restricted, often due to privacy concerns; only aggregated, robust and inefficient statistics derived from the data…
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…
Computing Bayes: From Then 'Til Now'
Gael M. Martin, David T. Frazier, Christian P. Robert
This paper takes the reader on a journey through the history of Bayesian computation, from the 18th century to the present day. Beginning with the one-dimensional integral first co…
The Importance Markov Chain
Charly Andral, Randal Douc, Hugo Marival +1
The Importance Markov chain is a novel algorithm bridging the gap between rejection sampling and importance sampling, moving from one to the other through a tuning parameter. Based…
50 shades of Bayesian testing of hypotheses
Christian P Robert
Hypothesis testing and model choice are quintessential questions for statistical inference and while the Bayesian paradigm seems ideally suited for answering these questions, it fa…
Evidence estimation in finite and infinite mixture models and applications
Adrien Hairault, Christian P. Robert, Judith Rousseau
Estimating the model evidence - or mariginal likelihood of the data - is a notoriously difficult task for finite and infinite mixture models and we reexamine here different Monte C…