class_docstr: The power transform as a link function:
  
  g(x) = x**power
docstr: Inverse of power transform
  
  g(x) = x**(1/self.power)
  
  INPUTS:
     z   -- linear predictors in GLM
  
  OUTPUTS: x
     x   -- mean parameters
docstr_tok: ["Inverse","of","power","transform","g","(","x",")","=","x","*","*","(","1\/self.power",")","INPUTS",":","z","--","linear","predictors","in","GLM","OUTPUTS",":","x","x","--","mean","parameters"]
code: def inverse(self, z):
      """
      Inverse of power transform
  
      g(x) = x**(1/self.power)
  
      INPUTS:
         z   -- linear predictors in GLM
  
      OUTPUTS: x
         x   -- mean parameters
  
      """
      return np.power(z, 1.0 / self.power)
  
imports: import numpy
  import scipy.stats
label_desc: Use image node_id 3 for calling the Power obj's underlying member method code with example usage: obj.inverse(z) and returns: np