class_docstr: asymmetric logistic model of Tawn 1988
  
  special case: a1=a2=1 : Gumbel
  
  restrictions:
   - theta in (0,1]
   - a1, a2 in [0,1]
code: def deriv2(self, t, a1, a2, theta):
      b = theta
      d2 = (
          (1 - b)
          * (a1 * t) ** (1 / b)
          * (a2 * (1 - t)) ** (1 / b)
          * ((a1 * t) ** (1 / b) + (a2 * (1 - t)) ** (1 / b)) ** (b - 2)
      ) / (b * (1 - t) ** 2 * t**2)
      return d2
  
imports: import numpy
  from scipy import stats
  from statsmodels.tools.numdiff import _approx_fprime_cs_scalar, approx_hess
label_desc: Use image node_id 4 for calling the AsymLogistic obj's underlying member method code with example usage: obj.deriv2(t, a1, a2, theta) and returns: d2