class_docstr: Marginal correlation effect sizes for FDR control.
  
  Parameters
  ----------
  parent : RegressionFDR
      The RegressionFDR instance to which this effect size is
      applied.
  
  Notes
  -----
  This class implements the marginal correlation approach to
  constructing test statistics for a knockoff analysis, as
  described under (1) in section 2.2 of the Barber and Candes
  paper.
class_docstr_tok: ["Marginal","correlation","effect","sizes","for","FDR","control",".","Parameters","--","--","--","--","--","parent",":","RegressionFDR","The","RegressionFDR","instance","to","which","this","effect","size","is","applied",".","Notes","--","--","-","This","class","implements","the","marginal","correlation","approach","to","constructing","test","statistics","for","a","knockoff","analysis",",","as","described","under","(","1",")","in","section","2.2","of","the","Barber","and","Candes","paper","."]
code: def stats(self, parent):
      s1 = np.dot(parent.exog1.T, parent.endog)
      s2 = np.dot(parent.exog2.T, parent.endog)
      return np.abs(s1) - np.abs(s2)
  
file_path: statsmodels/statsmodels/stats/knockoff_regeffects.py
imports: import numpy
label_desc: Use image node_id 1 for calling the CorrelationEffects obj's underlying member method code with example usage: obj.stats(parent) and returns: unknown