statsmodels.base.distributed_estimation.DistributedModel.fit_sequential

DistributedModel.fit_sequential(data_generator, fit_kwds, init_kwds_generator=None)[source]

Sequentially performs the distributed estimation using the corresponding DistributedModel

Parameters:
data_generatorgenerator

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_kwdsdict-like

Keywords needed for the model fitting.

init_kwds_generatorgenerator 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.

Last update: May 14, 2024