class_docstr: model of Huesler Reiss 1989
  
  special case:  a1=a2=1 : symmetric negative logistic of Galambos 1978
  
  restrictions:
   - lambda in (0,inf)
code: def evaluate(self, t, lamda):
      # if not np.all(self._check_args(lamda)):
      #    raise ValueError('invalid args')
  
      term = np.log((1.0 - t) / t) * 0.5 / lamda
  
      from scipy.stats import norm
  
      # use special if I want to avoid stats import
      transf = (1 - t) * norm._cdf(lamda + term) + t * norm._cdf(
          lamda - term
      )
      return transf
  
imports: import numpy
  from scipy import stats
  from statsmodels.tools.numdiff import _approx_fprime_cs_scalar, approx_hess
label_desc: Use image node_id 2 for calling the HR obj's underlying member method code with example usage: obj.evaluate(t, lamda) and returns: transf