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.
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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 Answers
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.

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I am not familiar with [Weibullization](https://en.wiktionary.org/wiki/Weibullization), but it sounds promising. – DifferentialPleiometry Oct 14 '21 at 16:16
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[Pauw *et al* 2010](https://www.researchgate.net/publication/268429861_Densities_of_composite_weibullized_generalized_gamma_variables) *prima facie* appears related. – DifferentialPleiometry Oct 14 '21 at 16:17