pymc.step_methods.Metropolis.__init__#

Metropolis.__init__(vars=None, *, S=None, proposal_dist=None, scaling=1.0, tune=True, tune_interval=100, model=None, mode=None, rng=None, initial_point=None, compile_kwargs=None, blocked=False)[source]#

Create an instance of a Metropolis stepper.

Parameters:
vars: list

List of value variables for sampler

S: standard deviation or covariance matrix

Some measure of variance to parameterize proposal distribution

proposal_dist: function

Function that returns zero-mean deviates when parameterized with S (and n). Defaults to normal.

scaling: scalar or array

Initial scale factor for proposal. Defaults to 1.

tune: bool

Flag for tuning. Defaults to True.

tune_interval: int

The frequency of tuning. Defaults to 100 iterations.

model: PyMC Model

Optional model for sampling step. Defaults to None (taken from context).

mode: string or `Mode` instance.

compilation mode passed to PyTensor functions

rng: RandomGenerator

An object that can produce be used to produce the step method’s Generator object. Refer to pymc.util.get_random_generator() for more information.