Please use this identifier to cite or link to this item: https://hdl.handle.net/10419/324755 
Authors: 
Year of Publication: 
2025
Series/Report no.: 
IHS Working Paper No. 60
Publisher: 
Institut für Höhere Studien - Institute for Advanced Studies (IHS), Vienna
Abstract: 
We propose a flexible, extensible family of distributions for testing Markov Chain Monte Carlo implementations. Distributions are created by nesting simple transformations, which allow various shapes, including multiple modes and fat tails. The resulting distributions can be sampled with high precision using quasi-random sequences, and have closed form (log) density and gradient at each point, making it possible to test gradient-based samplers without automatic differentiation
URL of the first edition: 
Creative Commons License: 
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Document Type: 
Working Paper

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