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There exists two parametrizations of the Gamma distribution : see https://en.wikipedia.org/wiki/Gamma_distribution
One with a shape and scale parameters and the other with a shape and rate parameters.
In order to be more comparable with other distributions defined in StatisKit.Core, I propose to use the first definition.
More generally should not we propose a location and a scale parameter for all continuous univariate distributions ?
It is always possible to define the cdf $F_{u,s}(x):=F((x-u)/s)$.
The advantage would be to obtain more comparable distributions.
The text was updated successfully, but these errors were encountered:
It seems that the Gamma has been described with a third parametrization in the GLM framework; see the book "Genralized Linear Models" of McCullagh and Nelder (1989).
Nevertheless, this third parametrization uses the scale parameter and use the inverse of the shape parameter k (used in the wikipedia version 1).
There exists two parametrizations of the Gamma distribution : see https://en.wikipedia.org/wiki/Gamma_distribution$F_{u,s}(x):=F((x-u)/s)$ .
One with a shape and scale parameters and the other with a shape and rate parameters.
In order to be more comparable with other distributions defined in StatisKit.Core, I propose to use the first definition.
More generally should not we propose a location and a scale parameter for all continuous univariate distributions ?
It is always possible to define the cdf
The advantage would be to obtain more comparable distributions.
The text was updated successfully, but these errors were encountered: