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| Auteurs principaux: | , |
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| Format: | Preprint |
| Publié: |
2024
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| Sujets: | |
| Accès en ligne: | https://arxiv.org/abs/2406.06851 |
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| _version_ | 1866916282581909504 |
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| author | Atchadé, Yves F. Jacob, Pierre E. |
| author_facet | Atchadé, Yves F. Jacob, Pierre E. |
| contents | This document presents methods to remove the initialization or burn-in bias from Markov chain Monte Carlo (MCMC) estimates, with consequences on parallel computing, convergence diagnostics and performance assessment. The document is written as an introduction to these methods for MCMC users. Some theoretical results are mentioned, but the focus is on the methodology. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_06851 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Unbiased Markov Chain Monte Carlo: what, why, and how Atchadé, Yves F. Jacob, Pierre E. Methodology This document presents methods to remove the initialization or burn-in bias from Markov chain Monte Carlo (MCMC) estimates, with consequences on parallel computing, convergence diagnostics and performance assessment. The document is written as an introduction to these methods for MCMC users. Some theoretical results are mentioned, but the focus is on the methodology. |
| title | Unbiased Markov Chain Monte Carlo: what, why, and how |
| topic | Methodology |
| url | https://arxiv.org/abs/2406.06851 |