![]() ![]() The reason I was interested in using the SciPy version is that the Scipy package defines a "percent point function" (ppf) which can be used to generate a set of random values from uniformly distributed probabilities (i.e. However, I've noticed that while the powerlaw python package seems to use this definition, uses a slightly different definition for powerlaw distributions and that is formula3 where alpha is positive and x is between 0 and 1 (inclusive), which we can rearrange if we let formula4 to the form formula5, which would match the form of formula2 (above) but with a negative sign in front of it, with the caveat that alpha would then be negative in the powerlaw version. I am trying to simulate random variables that are power law distributed based on my understanding of the definition in this Wikipedia article and several other resources where the consensus is that a "power law distributed random variable" has the probability density function (PDF) of the form formula1 and in particular, I'm interested in the case where x_min=1, which reduces to
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