5

The Amoroso distribution is a remarkable feat of abstraction as it exactly or asymptotically generalizes dozens of named probability distributions. Is there a published/pre-published treatment of multivariate Amoroso distributions? Either the cumulative density function (CDF) or the probability density function (PDF) would be acceptable answers.

DifferentialPleiometry
  • 2,274
  • 1
  • 11
  • 27
  • One might be able to find a joint distribution by using a copula, such as the maximum positive dependence copula. However, this seems unnatural to me. If it isn't too indulgent of me to require this, please avoid such a direct use of copulas. – DifferentialPleiometry Oct 09 '21 at 21:01

1 Answers1

3

This is so far not a full answer. The Amoroso distribution is a generalization of the generalized gamma distribution, obtained by parametrizing its range (by replacing $x$ with $x-a$ so the lower bound of the range is no longer 0). So how do we obtain the generalized gamma?

We can do that by Weibullizing a standard gamma distribution. Start with the Gamma distribution with density inn the form $$ f(x)\; dx = \frac{1}{\Gamma(\alpha)} \left(\frac{x}{\theta}\right)^\alpha e^{\frac{x}{\theta}} \; \frac{dx}{x} $$ Now introduce a new parameter $k$ by replacing $\frac{x}{\theta}$ with $\left(\frac{x}{\theta}\right)^k$ (and recalculate the normalizing factor). The result of this Weibullization is the generalized gamma distribution.

Now, there are multiple ways to define a multivariate gamma distribution, start with one of them and try Weibullization.

kjetil b halvorsen
  • 63,378
  • 26
  • 142
  • 467