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, **kwargs)[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