This is a compact implementation of the "control functional" method for Monte Carlo integration proposed in Oates, Chopin and Girolami, Journal of the Royal Statistical Society, Series B, 2017. The basic idea is that gradient information on the posterior distribution in Bayesian statistics can be used to better estimate integrals with respect to the posterior, via Stein's method.
Chris Oates (2023). Control Functionals (https://www.mathworks.com/matlabcentral/fileexchange/61755-control-functionals), MATLAB Central File Exchange. Retrieved .
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Fixed a typo in the pre-amble.
Improved the example usage in the pre-amble so that it generalises to d = 2,3.
In version 1.0 the likelihood function was incorrect. The wrong covariance matrix was used. This is now fixed.
Renamed zip folder