code: def summary(self, transformed=True):
      if self.ihessian is not None:
          return self.summary_with_hessian(transformed)
      else:
          return self.summary_without_hessian()
  
imports: import numpy
  from .output import TablePrinter
  from .tests import find_p_value
  from .inference import norm_post_sim
label_desc: Use image node_id 3 for calling the MLEResults obj's underlying member method code with example usage: obj.summary(transformed) and returns: self, self