For target density π and proposal density q, the Metropolis–Hastings acceptance probability is 1∧{π(y)q(y,x)/(π(x)q(x,y))}.
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- Metropolis–Hastings algorithm
- Markov chain Monte Carlo
- Bayesian statistics
- Statistical inference
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- Fixed-temperature law of simulated annealing
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- Preconditioned Crank–Nicolson algorithm
- Proposal distribution
- Pseudo-marginal Metropolis–Hastings algorithm
- Simulated annealing
- Surrogate Hamiltonian Monte Carlo
- Trans-dimensional annealing for penalized likelihood
- Weighted matching Markov chain
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