simuk.SBC

class simuk.SBC(model, num_simulations=1000, sample_kwargs=None, seed=None, data_dir=None)

Set up class for doing SBC.

Parameters:

• model (pymc.Model, bambi.Model or numpyro.infer.mcmc.MCMCKernel) – A PyMC, Bambi model or Numpyro MCMC kernel. If a PyMC model the data needs to be defined as mutable data.

• num_simulations (int) – How many simulations to run

• sample_kwargs (dict[str] -> Any) – Arguments passed to pymc.sample or bambi.Model.fit

• seed (int (optional)) – Random seed. This persists even if running the simulations is paused for whatever reason.

• data_dir (dict) – Keyword arguments passed to numpyro model, intended for use when providing an MCMC Kernel model.

Example

with pm.Model() as model:
    x = pm.Normal('x')
    y = pm.Normal('y', mu=2 * x, observed=obs)

sbc = SBC(model)
sbc.run_simulations()
sbc.plot_results()

Methods

run_simulations(*args, **kwargs)