code: def __init__(
      self,
      exog=None,
      endog=None,
      num_partitions=None,
      partition_id=None,
      factor=None,
      model_class=None,
      init_kwds=None,
      fit_kwds=None,
      estimation_method=None,
      estimation_kwds=None,
      join_method=None,
      join_kwds=None,
      results_class=None,
      results_kwds=None,
      **kw,
  ):
      super().__init__(
          _exog=exog,
          _endog=endog,
          _num_partitions=num_partitions,
          _partition_id=partition_id,
          _factor=factor,
          _model_class=model_class,
          _init_kwds=init_kwds,
          _fit_kwds=fit_kwds,
          _estimation_method=estimation_method,
          _estimation_kwds=estimation_kwds,
          _join_method=join_method,
          _join_kwds=join_kwds,
          _results_class=results_class,
          _results_kwds=results_kwds,
          **kw,
      )
  
imports: import pickle
  import cloudpickle
  from ....None import opcodes
  from ....core import OutputType, recursive_tile
  from ....core.context import get_context
  from ....core.operand import OperandStage, MergeDictOperand
  from ....serialization.serializables import KeyField, BytesField, DictField, Int32Field, Float32Field, FunctionField
  from ....utils import has_unknown_shape
label_desc: Use image node_id 1 to create a new StatsModelsTrain object from inherited base classes: MergeDictOperand with example: obj = StatsModelsTrain(exog, endog, num_partitions, partition_id, factor, model_class, init_kwds, fit_kwds, estimation_method, estimation_kwds, join_method, join_kwds, results_class, results_kwds)