Optimal scaling of random-walk Metropolis algorithms using Bayesian
large-sample asymptotics

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Optimal scaling of random-walk Metropolis algorithms using Bayesian large-sample asymptotics

13 April 2021

Sebastian M. Schmon

Philippe Gagnon

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Papers citing "Optimal scaling of random-walk Metropolis algorithms using Bayesian large-sample asymptotics"

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Title
Accelerating Bayesian inference for stochastic epidemic models using incidence data Andrew Golightly L. Wadkin Sam A. Whitaker A. Baggaley N. G. Parker T. Kypraios 58 6 0 27 Mar 2023
Improving multiple-try Metropolis with local balancing Philippe Gagnon Florian Maire Giacomo Zanella 78 11 0 21 Nov 2022
Amortised Likelihood-free Inference for Expensive Time-series Simulators with Signatured Ratio Estimation Joel Dyer Patrick W Cannon Sebastian M. Schmon 101 9 0 23 Feb 2022
Black-box Bayesian inference for economic agent-based models Joel Dyer Patrick W Cannon J. Farmer Sebastian M. Schmon 107 24 0 01 Feb 2022
Approximate Bayesian Computation with Path Signatures Joel Dyer Patrick W Cannon Sebastian M. Schmon 115 16 0 23 Jun 2021
Optimal Scaling of MCMC Beyond Metropolis Sanket Agrawal Dootika Vats K. Łatuszyński Gareth O. Roberts 73 11 0 05 Apr 2021