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              "value": "The Generalized Hyperbolic Distribution is defined as the normal variance-mean mixture with Generalized Inverse Gaussian distribution as the mixing distribution. The \"hyperbolic\" characterization refers to the fact that the shape of the log-probability distribution can be described as a hyperbola. Hyperbolic distributions are sometime referred to as semi-fat tailed because their probability density decrease slower than \"sub-hyperbolic\" distributions (e.g. normal distribution, whose log-probability decreases quadratically), but faster than other \"extreme value\" distributions (e.g. "
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              "value": " distribution, whose log-probability decreases logarithmically)."
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              "value": "Different parameterizations exist in the literature; SciPy implements the \"4th parametrization\" in Prause (1999)."
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