pymc.step_methods.hmc.HamiltonianMC#

class pymc.step_methods.hmc.HamiltonianMC(*args, **kwargs)[source]#

A sampler for continuous variables based on Hamiltonian mechanics.

See NUTS sampler for automatically tuned stopping time and step size scaling.

Methods

HamiltonianMC.__init__([vars, path_length, ...])

Set up the Hamiltonian Monte Carlo sampler.

HamiltonianMC.astep(q0)

Perform a single HMC iteration.

HamiltonianMC.competence(var, has_grad)

Check how appropriate this class is for sampling a random variable.

HamiltonianMC.reset([start])

HamiltonianMC.reset_tuning([start])

HamiltonianMC.set_rng(rng)

HamiltonianMC.step(point)

Perform a single step of the sampler.

HamiltonianMC.stop_tuning()

Attributes

default_blocked

name

sampling_state

stats_dtypes

A list containing <=1 dictionary that maps stat names to dtypes.

stats_dtypes_shapes

Maps stat names to dtypes and shapes.

vars

Variables that the step method is assigned to.

integrator