Our goal is to build a filtering approach that approximates not only the mean and covariance but the higher order moments of the posterior with high accuracy ...

Filtering is an approach for incorporating observed data into time-evolving systems. Instead of a family of Dirac delta masses that is widely used in Monte ...

Oct 10, 2024 · Adaptive approximation of higher order posterior statistics Online resource. BrowZine Book Icon Available at BrowZine ...

Adaptive approximation of higher order posterior statistics. Research output: Journal Publications and Reviews › RGC 21 - Publication in refereed journal.

Abstract. Approximate Bayesian Computation (ABC) methods are increasingly used for inference in situations in which the likelihood function is either compu-.

In the latter ABC methods, SMC is used in order to automatically, sequentially refine posterior approximations to be used to generate proposals for further ...

Aug 6, 2020 · We address this problem by developing an automatic, adaptive algorithm that chooses weights for each summary statistic. Our algorithm aims to ...

Apr 6, 2023 · Minimum Bayes factors are commonly used to transform two-sided p-values to lower bounds on the posterior probability of the null hypothesis.

In this article, I introduce the concept of adaptive tree proposals for unrooted topologies, that is, tree proposals adapting to the posterior distribution as ...

Sep 24, 2020 · This article proposes a novel adaptive design algorithm that can be used to find optimal treatment allocations in N-of-1 clinical trials.