code: def __call__(self, exog):
      if isinstance(exog, (DATAFRAME_TYPE, SERIES_TYPE)):
          self._output_types = [OutputType.series]
          kwargs = dict(
              shape=exog.shape[:1],
              index_value=exog.index_value,
              dtype=np.dtype("float"),
          )
      else:
          self._output_types = [OutputType.tensor]
          kwargs = dict(
              shape=exog.shape[:1],
              dtype=np.dtype("float"),
          )
      return self.new_tileable([exog], **kwargs)
  
file_path: mars/mars/learn/contrib/statsmodels/predict.py
imports: import pickle
  import numpy
  from ....None import opcodes
  from ....core import OutputType, recursive_tile
  from ....dataframe.core import DATAFRAME_TYPE, SERIES_TYPE
  from ....serialization.serializables import BytesField, DictField, TupleField
  from ...operands import LearnOperand, LearnOperandMixin
label_desc: Use image node_id 5 for calling the StatsModelsPredict obj's underlying member method code with example usage: obj.__call__(exog) and returns: self