rxmc.param_sampling.MetropolisHastingsSampler#

class rxmc.param_sampling.MetropolisHastingsSampler(params: list[Parameter], prior, starting_location: ndarray, proposal: ProposalDistribution)[source]#

Bases: Sampler

Metropolis-Hastings sampler with a fixed proposal distribution.

Parameters:

  • params (list of Parameter) – Parameters to sample.

  • prior (object) – Prior distribution with a callable logpdf(x) method.

  • starting_location (np.ndarray, shape (ndim,)) – Initial parameter vector.

  • proposal (ProposalDistribution) – Callable proposal distribution. Must accept (x, rng) and return a proposed parameter vector.

__init__(params: list[Parameter], prior, starting_location: ndarray, proposal: ProposalDistribution)[source]#

Methods

__init__(params, prior, starting_location, ...)

batch_acceptance_fractions()

Acceptance fraction for each completed batch.

most_recent_batch_acceptance_fraction()

Acceptance fraction of the most recent batch.

overall_acceptance_fraction()

Overall acceptance fraction across all completed batches.

record_batch(n_steps, n_accepted, chain, ...)

Append a completed batch to the running chain.

sample(n_steps, starting_location, rng, ...)

Run the sampling algorithm for one batch.