MMM.fit

MMM.fit(X, y=None, progressbar=None, random_seed=None, **kwargs)

Fit a model using the data passed as a parameter.

Parameters:

Xarray_like | array, shape (n_obs, n_features)

The training input samples. If scikit-learn is available, array-like, otherwise array.

yarray_like | array, shape (n_obs,)

The target values (real numbers). If scikit-learn is available, array-like, otherwise array.

progressbarbool, optional

Specifies whether the fit progress bar should be displayed. Defaults to True.

random_seedRandomState, optional

Provides the sampler with an initial random seed for reproducible samples.

**kwargsdict

Additional keyword arguments passed to the sampler.

Returns:

az.InferenceData

The inference data from the fitted model.

Examples

>>> model = MyModel()
>>> idata = model.fit(X, y, progressbar=True)