It is known that if X is uniformly distributed modulo 1 and Y is an arbitrary
random variable independent of X then Y+X is also uniformly distributed modulo
- We prove a converse for any continuous random variable Y (or a reasonable
approximation to a continuous random variable) so that if X and Y+X are equally
distributed modulo 1 and Y is independent of X then X is uniformly distributed
modulo 1 (or approximates the uniform distribution equally reasonably). This
translates into a characterization of Benford’s law through a generalization of
scale-invariance: from multiplication by a constant to multiplication by an
independent random variable.
We also show a base-invariance characterization: if a positive continuous
random variable has the same significand distribution for two bases then it is
Benford for both bases. The set of bases for which a random variable is Benford
is characterized through characteristic functions.