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Re:Benford's Law by hyperbovine on Sunday February 16, 2020 @02:37AM (#22340404)
The max entropy distribution over (-oo,+oo) is usually taken to be either Gaussian or Laplace (two sided exponential), depending on moment conditions. There is no such thing as a uniform distribution over the real line.
Re:Benford's Law by BenoitEssiambre on Sunday February 16, 2020 @08:35AM (#22341469)
Of course there is. It's an improper prior (doesn't sum up to one), see link above. Theoretically the Gaussian is only maximum entropy given a mean and stddev. An infinite uniform is maxent without any knowledge of mean and stddev.

In practice though you can use a wide Gaussian if it is more mathematically convenient and get about the same results.

Re:Benford's Law by hyperbovine on Sunday February 16, 2020 @03:57PM (#22343709)
The entropy of any improper prior diverges. There is no point in arguing over which one maximizes entropy; they all do, vacuously. Max entropy is not useful for discriminating amongst probability distributions unless you require them to actually be probability distributions.
Re:Benford's Law by baxtr on Sunday February 16, 2020 @03:08AM (#22340497)
Side note: great how you spell infinity. Never saw this before. So simple and smart
Re:Benford's Law by polyphonicist on Sunday February 16, 2020 @04:31AM (#22340727)
Came here to say the same thing. Certainly haven't seen such depiction of infinity earlier. But this is a nice way. I am going to use it myself.
Re:Benford's Law by mkl on Sunday February 16, 2020 @07:00AM (#22341155)
It's used as the symbol for infinity in Sympy, and probably other (and older) computer algebra systems.