تقرير
Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning
| العنوان: | Incorporating Local Step-Size Adaptivity into the No-U-Turn Sampler using Gibbs Self Tuning |
|---|---|
| المؤلفون: | Bou-Rabee, Nawaf, Carpenter, Bob, Kleppe, Tore Selland, Marsden, Milo |
| سنة النشر: | 2024 |
| المجموعة: | Mathematics Statistics |
| مصطلحات موضوعية: | Statistics - Methodology, Mathematics - Probability, Statistics - Computation |
| الوصف: | Adapting the step size locally in the no-U-turn sampler (NUTS) is challenging because the step-size and path-length tuning parameters are interdependent. The determination of an optimal path length requires a predefined step size, while the ideal step size must account for errors along the selected path. Ensuring reversibility further complicates this tuning problem. In this paper, we present a method for locally adapting the step size in NUTS that is an instance of the Gibbs self-tuning (GIST) framework. Our approach guarantees reversibility with an acceptance probability that depends exclusively on the conditional distribution of the step size. We validate our step-size-adaptive NUTS method on Neal's funnel density and a high-dimensional normal distribution, demonstrating its effectiveness in challenging scenarios. Comment: for companion code, see https://github.com/bob-carpenter/adaptive-hmc |
| نوع الوثيقة: | Working Paper |
| URL الوصول: | http://arxiv.org/abs/2408.08259 |
| رقم الأكسشن: | edsarx.2408.08259 |
| قاعدة البيانات: | arXiv |
| الوصف غير متاح. |