2 citations · 3 across the 4 of their papers we have counts for
4 papers
Stein's Method Meets Computational Statistics: A Review of Some Recent Developments
Andreas Anastasiou, Alessandro Barp, François-Xavier Briol +11
Stein's method compares probability distributions through the study of a class of linear operators called Stein operators. While mainly studied in probability and used to underpin…
The Wasserstein Impact Measure (WIM): a generally applicable, practical tool for quantifying prior impact in Bayesian statistics
Fatemeh Ghaderinezhad, Christophe Ley, Ben Serrien
The prior distribution is a crucial building block in Bayesian analysis, and its choice will impact the subsequent inference. It is therefore important to have a convenient way to…
Simple variance bounds with applications to Bayesian posteriors and intractable distributions
Fraser Daly, Fatemeh Ghaderinezhad, Christophe Ley +1
Using coupling techniques based on Stein's method for probability approximation, we revisit classical variance bounding inequalities of Chernoff, Cacoullos, Chen and Klaassen. Taki…
A general measure of the impact of priors in Bayesian statistics via Stein's Method
Fatemeh Ghaderinezhad, Christophe Ley
We propose a measure of the impact of any two choices of prior distributions by quantifying the Wasserstein distance between the respective resulting posterior distributions at any…