class_docstr: The power transform as a link function:
  
  g(x) = x**power
docstr: Power transform
  
  g(x) = x**self.power
  
  INPUTS:
     x   -- mean parameters
  
  OUTPUTS: z
     z   -- power transform of x
docstr_tok: ["Power","transform","g","(","x",")","=","x","*","*","self.power","INPUTS",":","x","--","mean","parameters","OUTPUTS",":","z","z","--","power","transform","of","x"]
code: def __call__(self, x):
      """
      Power transform
  
      g(x) = x**self.power
  
      INPUTS:
         x   -- mean parameters
  
      OUTPUTS: z
         z   -- power transform of x
  
      """
  
      return np.power(x, self.power)
  
imports: import numpy
  import scipy.stats
label_desc: Use image node_id 2 for calling the Power obj's underlying member method code with example usage: obj.__call__(x) and returns: np