Journal: The European Physical Journal. C, Particles and Fields

Article Title: Testing T2K’s Bayesian constraints with priors in alternate parameterisations

doi: 10.1140/epjc/s10052-025-14836-0

Figure Lengend Snippet: Ratio of the largest over smallest weight applied to the MCMC chains when producing each prior. The ratios are small because the regions of parameter space which would receive the most extreme weights are excluded by the solar and/or T2K constraints. These ratios act as an upper bound for the amplification of the error in the MCMC approximation of the posterior due to the reweighing. The colors indicate the flavour pair of the prior and the shapes indicate the mass pair

Article Snippet: The Asimov B MCMC chain uses vastly different parameter values (though still consistent with existing data) and serves to verify that the small difference in the posteriors is a consequence of T2K’s strong constraining power and not an artefact of the region of parameter space favoured by current data.

Techniques: Amplification

Journal: The European Physical Journal. C, Particles and Fields

Article Title: Testing T2K’s Bayesian constraints with priors in alternate parameterisations

doi: 10.1140/epjc/s10052-025-14836-0

Figure Lengend Snippet: Ratio of the largest over smallest weight applied to the MCMC chains when producing each prior. The ratios are small because the regions of parameter space which would receive the most extreme weights are excluded by the solar and/or T2K constraints. These ratios act as an upper bound for the amplification of the error in the MCMC approximation of the posterior due to the reweighing. The colors indicate the flavour pair of the prior and the shapes indicate the mass pair

Article Snippet: The simulated data for the Asimov A MCMC chain were generated using parameter values similar to T2K’s best fit, and serve to confirm that these results are not an artefact of some undetected tensions between T2K samples.

Techniques: Amplification

Journal: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

Article Title: Bayesian inference informed by parameter subset selection for a minimal PBPK brain model

doi: 10.1098/rsta.2024.0219

Figure Lengend Snippet: Posterior mean, posterior standard deviation and ESS of the MCMC chain for each parameter obtained with η = 2.5 × 10 − 8 .

Article Snippet: The DRAM algorithm is implemented in MATLAB using the MCMC toolbox, as outlined in [ , ].

Techniques: Standard Deviation

Journal: Philosophical transactions. Series A, Mathematical, physical, and engineering sciences

Article Title: Bayesian inference informed by parameter subset selection for a minimal PBPK brain model

doi: 10.1098/rsta.2024.0219

Figure Lengend Snippet: Posterior mean, posterior standard deviation and ESS of the MCMC chain for each parameter obtained with η = 2.5 × 10 − 8 .

Article Snippet: The DRAM algorithm is implemented in MATLAB using the MCMC toolbox, as outlined in [ , ].

Techniques: Standard Deviation