Construct · 1 fields · 1 citations

Metropolis-Hastings algorithm: a standalone construct

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Bayesian statistics

a Markov chain Monte Carlo method that proposes moves from an arbitrary distribution and accepts them with a probability that leaves the target distribution invariant.

In Bayesian statistics, Metropolis-Hastings algorithm refers to a Markov chain Monte Carlo method that proposes moves from an arbitrary distribution and accepts them with a probability that leaves the target distribution invariant. This meaning comes from Hastings (1970) in Biometrika.[1]

Unit
Recovery means
Measured by

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Nearby constructs

chain3 fields · 3 citationsjingle · one word, three constructs distribution2 fields · 2 citationsjingle · one word, two constructs Markov chain Monte Carlo1 fields · 1 citationsanchor · a standalone construct

References

Hastings, W. K. (1970). Monte Carlo sampling methods using Markov chains and their applications. Biometrika, 57(1), 97-109. https://doi.org/10.1093/biomet/57.1.97

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