18 citations · 67 across the 26 of their papers we have counts for
5 papers · 1 filter
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…
Computing Bayes: Bayesian Computation from 1763 to the 21st Century
Gael M. Martin, David T. Frazier, Christian P. Robert
The Bayesian statistical paradigm uses the language of probability to express uncertainty about the phenomena that generate observed data. Probability distributions thus characteri…
Efficient Bayesian synthetic likelihood with whitening transformations
Jacob W. Priddle, Scott A. Sisson, David T. Frazier +1
Likelihood-free methods are an established approach for performing approximate Bayesian inference for models with intractable likelihood functions. However, they can be computation…
Auxiliary Likelihood-Based Approximate Bayesian Computation in State Space Models
Gael M. Martin, Brendan P. M. McCabe, David T. Frazier +2
A computationally simple approach to inference in state space models is proposed, using approximate Bayesian computation (ABC). ABC avoids evaluation of an intractable likelihood b…
On Consistency of Approximate Bayesian Computation
David T. Frazier, Gael M. Martin, Christian P. Robert
Approximate Bayesian computation (ABC) methods have become increasingly prevalent of late, facilitating as they do the analysis of intractable, or challenging, statistical problems…