1 code implementation • 29 Jan 2024 • Philip Schär, Michael Habeck, Daniel Rudolf
The performance of Markov chain Monte Carlo samplers strongly depends on the properties of the target distribution such as its covariance structure, the location of its probability mass and its tail behavior.
1 code implementation • 8 Feb 2023 • Philip Schär, Michael Habeck, Daniel Rudolf
Polar slice sampling (Roberts & Rosenthal, 2002) is a Markov chain approach for approximate sampling of distributions that is difficult, if not impossible, to implement efficiently, but behaves provably well with respect to the dimension.
