9 citations · 23 across the 9 of their papers we have counts for
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stat.ME2025
Improved MCMC with active subspaces
Leonardo Ripoli, Richard G. Everitt
Constantine et al. (2016) introduced a Metropolis-Hastings (MH) approach that target the active subspace of a posterior distribution: a linearly projected subspace that is informed…
stat.ME2024
Ensemble Kalman inversion approximate Bayesian computation
Richard G Everitt
Approximate Bayesian computation (ABC) is the most popular approach to inferring parameters in the case where the data model is specified in the form of a simulator. It is not poss…
stat.ME2023
Bayesian Inference of Reproduction Number from Epidemiological and Genetic Data Using Particle MCMC
Alicia Gill, Jere Koskela, Xavier Didelot +1
Inference of the reproduction number through time is of vital importance during an epidemic outbreak. Typically, epidemiologists tackle this using observed prevalence or incidence…