distribution tail_bound cleanup
@@ -72,7 +72,7 @@ class Lognormal():
size=N))
return draws
- def approx(self, N, tail_N=0, tail_bound=[0.02,0.98], tail_order=np.e):
+ def approx(self, N, tail_N=0, tail_bound=None, tail_order=np.e):
'''
Construct a discrete approximation to a lognormal distribution with underlying
normal distribution N(mu,sigma). Makes an equiprobable distribution by
@@ -99,6 +99,7 @@ class Lognormal():
Probability associated with each point in array of discrete
points for discrete probability mass function.
'''
+ tail_bound = tail_bound if tail_bound is not None else [0.02, 0.98]
# Find the CDF boundaries of each segment
if self.sigma > 0.0:
if tail_N > 0:
