This file tries to take aspects of the Bayesian workflow paper by Gelman and colleagues and apply them to an example scenario in experimental psychology / cognitive neuroscience. The workflow that I ...

r_nom = data.frequency_ratio; % Nominal values of the dimensionless input frequency ratios coulomb_force = flip(driving_force .* data.force_ratio); % Nominal values ...

One of the main obstacles to the routine implementation of Bayesian methods has been the absence of efficient algorithms for carrying out the computational tasks implicit in the Bayesian approach. In ...

Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 40, No. 4 (1991), pp. 365-372 (8 pages) A numerical approach to Bayesian prediction for the two-parameter Weibull ...

Abstract: Bayesian optimization is commonly used to optimize black-box functions associated with simulations in engineering and science. Bayesian optimization contains two essential components: the ...