class_docstr: Class to contain model results
  
  Parameters
  ----------
  model : class instance
      Class instance for model used for distributed data,
      this particular instance uses fake data and is really
      only to allow use of methods like predict.
  params : ndarray
      Parameter estimates from the fit model.
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docstr: Calls self.model.predict for the provided exog.  See
  Results.predict.
  
  Parameters
  ----------
  exog : array_like NOT optional
      The values for which we want to predict, unlike standard
      predict this is NOT optional since the data in self.model
      is fake.
  *args :
      Some models can take additional arguments. See the
      predict method of the model for the details.
  **kwargs :
      Some models can take additional keywords arguments. See the
      predict method of the model for the details.
  
  Returns
  -------
      prediction : ndarray, pandas.Series or pandas.DataFrame
      See self.model.predict
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code: def predict(self, exog, *args, **kwargs):
      """Calls self.model.predict for the provided exog.  See
      Results.predict.
  
      Parameters
      ----------
      exog : array_like NOT optional
          The values for which we want to predict, unlike standard
          predict this is NOT optional since the data in self.model
          is fake.
      *args :
          Some models can take additional arguments. See the
          predict method of the model for the details.
      **kwargs :
          Some models can take additional keywords arguments. See the
          predict method of the model for the details.
  
      Returns
      -------
          prediction : ndarray, pandas.Series or pandas.DataFrame
          See self.model.predict
      """
  
      return self.model.predict(self.params, exog, *args, **kwargs)
  
imports: from statsmodels.base.elastic_net import RegularizedResults
  from statsmodels.stats.regularized_covariance import _calc_nodewise_row, _calc_nodewise_weight, _calc_approx_inv_cov
  from statsmodels.base.model import LikelihoodModelResults
  from statsmodels.regression.linear_model import OLS
  import numpy
label_desc: Use image node_id 2 for calling the DistributedResults obj's underlying member method code with example usage: obj.predict(exog) and returns: self