Metropolis-Hastings algorithm
GPTKB entity
Statements (33)
| Predicate | Object |
|---|---|
| gptkbp:instanceOf |
Markov chain
|
| gptkbp:application |
computational biology
econometrics statistical physics image analysis machine learning models Bayesian parameter estimation |
| gptkbp:category |
randomized algorithm
stochastic algorithm |
| gptkbp:field |
gptkb:machine_learning
computational physics statistics Bayesian inference |
| gptkbp:generalizes |
gptkb:Metropolis_algorithm
|
| https://www.w3.org/2000/01/rdf-schema#label |
Metropolis-Hastings algorithm
|
| gptkbp:introducedIn |
1953
|
| gptkbp:namedAfter |
gptkb:Nicholas_Metropolis
gptkb:W._K._Hastings |
| gptkbp:output |
Markov chain
|
| gptkbp:property |
ergodicity
detailed balance asymptotic convergence to target distribution |
| gptkbp:relatedTo |
gptkb:Monte_Carlo_method
gptkb:Gibbs_sampling Markov chain |
| gptkbp:requires |
proposal distribution
acceptance probability |
| gptkbp:step |
accept or reject proposal
compute acceptance ratio propose new state |
| gptkbp:usedFor |
sampling from probability distributions
|
| gptkbp:bfsParent |
gptkb:Markov_chain
|
| gptkbp:bfsLayer |
5
|