| Display title | Metropolis–Hastings algorithm |
| Default sort key | Metropolis-Hastings Algorithm |
| Page length (in bytes) | 30,665 |
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| Page ID | 206678 |
| Page content language | en - English |
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| Page creator | imported>Scavis2 |
| Date of page creation | 00:37, 7 February 2024 |
| Latest editor | imported>Scavis2 |
| Date of latest edit | 00:37, 7 February 2024 |
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Description | Content |
Article description: (description)
This attribute controls the content of the description and og:description elements. | In statistics and statistical physics, the Metropolis–Hastings algorithm is a Markov chain Monte Carlo (MCMC) method for obtaining a sequence of random samples from a probability distribution from which direct sampling is difficult. This sequence can be used to approximate the distribution (e.g. to generate... |
