pymc.step_methods.hmc.HamiltonianMC

class pymc.step_methods.hmc.HamiltonianMC(*args, **kwargs)

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