Gamma distribution

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Gamma distribution.

This distribution is a continuous function of biased character, that is, where the modal value does not correspond to the mean value. The Gamma distribution is a generalization of the exponential distribution, and is used in general to model random variables that represent the time in which an event occurs a certain number of times.

The pseudo-random generated by the application are an approximation (G. Marsaglia and W. Tsang) with a single input parameter called “shape”, which must be a positive real number. From version 3.2 it is possible to describe gamma functions with any standard deviation (using the second parameter named scale).

Input parameters:

  • Shape. This parameter defines the shape of the distribution. You can take as a value any number greater than zero, from field of real numbers.
  • Scale. This second parameter allows you to scale the resulting values ​​from the standard Gamma distribution, where this parameter is always 1. In this way it is possible to generate pseudo-random values with the same shape but with a greater standard deviation.

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