تقرير
Posterior exploration for computationally intensive forward models
العنوان: | Posterior exploration for computationally intensive forward models |
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المؤلفون: | Lykkegaard, Mikkel B., Fox, Colin, Higdon, Dave, Reese, C. Shane, Moulton, J. David |
سنة النشر: | 2024 |
المجموعة: | Statistics |
مصطلحات موضوعية: | Statistics - Computation |
الوصف: | In this chapter, we address the challenge of exploring the posterior distributions of Bayesian inverse problems with computationally intensive forward models. We consider various multivariate proposal distributions, and compare them with single-site Metropolis updates. We show how fast, approximate models can be leveraged to improve the MCMC sampling efficiency. Comment: To appear in the Handbook of Markov Chain Monte Carlo (2nd edition) |
نوع الوثيقة: | Working Paper |
URL الوصول: | http://arxiv.org/abs/2405.00397 |
رقم الأكسشن: | edsarx.2405.00397 |
قاعدة البيانات: | arXiv |
الوصف غير متاح. |