code: def REGR(**kwargs):
      """REGR class for Regression based thresholder.
  
      Use the regression to evaluate a non-parametric means
      to threshold scores generated by the decision_scores where outliers
      are set to any value beyond the y-intercept value of the linear fit.
  
      Parameters
      ----------
  
      method : {'siegel', 'theil'}, optional (default='siegel')
           Regression based method to calculate the y-intercept
  
           - 'siegel': implements a method for robust linear regression using repeated medians
           - 'theil':  implements a method for robust linear regression using paired values
  
      random_state : int, optional (default=1234)
           random seed for the normal distribution. Can also be set to None
  
      """
  
      from pythresh.thresholds.regr import REGR as REGR_thres
  
      return REGR_thres(**kwargs)
  
label_desc: Use image node_id 24 for calling a global function with example usage: REGR() and returns: REGR_thres