class_docstr: Prediction results for GLM.
  
  This results class is used for backwards compatibility for
  `get_prediction` with GLM. The new PredictionResults classes dropped the
  `_mean` post fix in the attribute names.
class_docstr_tok: ["Prediction","results","for","GLM",".","This","results","class","is","used","for","backwards","compatibility","for","`","get_prediction","`","with","GLM",".","The","new","PredictionResults","classes","dropped","the","`","_mean","`","post","fix","in","the","attribute","names","."]
code: def __init__(
      self,
      predicted_mean,
      var_pred_mean,
      var_resid=None,
      df=None,
      dist=None,
      row_labels=None,
      linpred=None,
      link=None,
  ):
      # TODO: is var_resid used? drop from arguments?
      self.predicted = predicted_mean
      self.var_pred = var_pred_mean
      self.df = df
      self.var_resid = var_resid
      self.row_labels = row_labels
      self.linpred = linpred
      self.link = link
  
      if dist is None or dist == "norm":
          self.dist = stats.norm
          self.dist_args = ()
      elif dist == "t":
          self.dist = stats.t
          self.dist_args = (self.df,)
      else:
          self.dist = dist
          self.dist_args = ()
  
imports: import numpy
  from scipy import stats
  import pandas
label_desc: Use image node_id 1 to create a new PredictionResultsMean object from inherited base classes: PredictionResultsBase with example: obj = PredictionResultsMean(predicted_mean, var_pred_mean, var_resid, df, dist, row_labels, linpred, link)