class_docstr: Results class for predictions.
  
  Parameters
  ----------
  predicted_mean : ndarray
      The array containing the prediction means.
  var_pred_mean : ndarray
      The array of the variance of the prediction means.
  var_resid : ndarray
      The array of residual variances.
  df : int
      The degree of freedom used if dist is 't'.
  dist : {'norm', 't', object}
      Either a string for the normal or t distribution or another object
      that exposes a `ppf` method.
  row_labels : list[str]
      Row labels used in summary frame.
class_docstr_tok: ["Results","class","for","predictions",".","Parameters","--","--","--","--","--","predicted_mean",":","ndarray","The","array","containing","the","prediction","means",".","var_pred_mean",":","ndarray","The","array","of","the","variance","of","the","prediction","means",".","var_resid",":","ndarray","The","array","of","residual","variances",".","df",":","int","The","degree","of","freedom","used","if","dist","is","'t","'",".","dist",":","{","'norm","'",",","'t","'",",","object","}","Either","a","string","for","the","normal","or","t","distribution","or","another","object","that","exposes","a","`","ppf","`","method",".","row_labels",":","list","[","str","]","Row","labels","used","in","summary","frame","."]
code: def se_mean(self):
      return self.se
  
file_path: statsmodels/statsmodels/regression/_prediction.py
imports: import numpy
  from scipy import stats
  import pandas
label_desc: Use image node_id 3 for calling the PredictionResults obj's underlying member method code with example usage: obj.se_mean() and returns: self