Interface | Description |
---|---|
SamplingAlgorithm | |
SimulatedAnnealing.AnnealingSchedule |
An annealing schedule determines how T (temperature) changes as
a function of the current iteration number (i.e.
|
Class | Description |
---|---|
Hamiltonian |
Hamiltonian Monte Carlo is a method for obtaining samples from a probability
distribution with the introduction of a momentum variable.
|
MetropolisHastings |
Metropolis Hastings is a Markov Chain Monte Carlo method for obtaining samples from a probability distribution
|
MetropolisHastings.Sampler | |
NetworkSamplesGenerator | |
NUTS |
Algorithm 6: "No-U-Turn Sampler with Dual Averaging".
|
SimulatedAnnealing |
Simulated Annealing is a modified version of Metropolis Hastings that causes the MCMC random walk to
tend towards the Maximum A Posteriori (MAP)
|