15 citations · 61 across the 20 of their papers we have counts for
8 papers · 1 filter
A review of Approximate Bayesian Computation methods via density estimation: inference for simulator-models
Clara Grazian, Yanan Fan
This paper provides a review of Approximate Bayesian Computation (ABC) methods for carrying out Bayesian posterior inference, through the lens of density estimation. We describe se…
High-dimensional ABC
D. J. Nott, V. M. -H. Ong, Y. Fan +1
This Chapter, "High-dimensional ABC", is to appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). It details the main ideas and concepts behind extending A…
Extending approximate Bayesian computation methods to high dimensions via a Gaussian copula model
Jingjing Li, David J. Nott, Yanan Fan +1
Approximate Bayesian computation (ABC) refers to a family of inference methods used in the Bayesian analysis of complex models where evaluation of the likelihood is difficult. Conv…
Approximate Bayesian Computation via Regression Density Estimation
Y. Fan, D. J. Nott, S. A. Sisson
Approximate Bayesian computation (ABC) methods, which are applicable when the likelihood is difficult or impossible to calculate, are an active topic of current research. Most curr…
Simultaneous adjustment of bias and coverage probabilities for confidence intervals
P. Menendez, Y. Fan, P. H. Garthwaite +1
A new method is proposed for the correction of confidence intervals when the original interval does not have the correct nominal coverage probabilities in the frequentist sense. Th…
Discussions on Fernhead and Prangle (2012)
D. J. Nott, Y. Fan, S. A. Sisson
Two contributions to the discussion of Fearnhead P. and D. Prangle (2012). Constructing summary statistics for approximate Bayesian computation: Semi-automatic approx- imate Bayesi…