statsmodels.base.distributed_estimation.DistributedModel.fit_joblib¶
method
-
DistributedModel.
fit_joblib
(data_generator, fit_kwds, parallel_backend, init_kwds_generator=None)[source]¶ Performs the distributed estimation in parallel using joblib
Parameters: data_generator : generator
A generator that produces a sequence of tuples where the first element in the tuple corresponds to an endog array and the element corresponds to an exog array.
fit_kwds : dict-like
Keywords needed for the model fitting.
parallel_backend : None or joblib parallel_backend object
used to allow support for more complicated backends, ex: dask.distributed
init_kwds_generator : generator or None
Additional keyword generator that produces model init_kwds that may vary based on data partition. The current usecase is for WLS and GLS
Returns: join_method result. For the default, _join_debiased, it returns a
p length array.