I recently came across the following distribution $$ \Pr(X\le x)=e^{\tfrac{1}{a}-\tfrac{1}{x}}\left(\dfrac{a}{x}\right)^{\tfrac{1}{a}},\; 0\le x< a, $$ and the cdf is 0 for all $x\lt 0$ and 1 for all $x\ge a$; here $a\gt 0$ is a parameter. Is this distribution a special case of some known distribution family, and if so, which one? It seems to be a truncated version of the Frechet distribution.
1 Answers
It's unusual.
Let $\beta = 1/a$ and $Y = 1/X$ (supported on the interval $(\beta,\infty)$) so that, exploiting the continuity of this distribution, $$\Pr(Y\le y) = \Pr(X \ge 1/y) = \Pr(X \gt 1/y) = 1 - C(\beta)y^{\beta}e^{-y}$$
where $C(\beta)\beta^\beta e^{-\beta} = 1.$
Differentiating with respect to $y$ gives the density function defined on $(\beta,\infty)$ in the form
$$f_Y(y) = C(\beta)\left(\beta y^{\beta-1} - y^{\beta}\right)e^{-y}.$$
This is a signed mixture of two truncated Gamma densities with shape parameters $\beta$ and $\beta+1$ and unit scale parameter. Such (untruncated) mixtures can arise as sums of Gamma distributions, as shown at https://stats.stackexchange.com/a/72486/919, so with a bit of algebra you should be able to express this as the truncation of a sum of two Gammas.
These characterizations don't hint at any common parametric family of distributions, so $X = 1/Y$ isn't likely to be part of such a family, either.
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1Although this nearly does not affect the text of the answer, there seem to be a typo in the formula for the density. I would find $\beta$ and $\beta - 1$ for the shapes. – Yves Sep 30 '22 at 08:34
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I see, thank you. – Jeff Sep 30 '22 at 09:44
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@Yves thank you--that's correct and I will fix it immediately. – whuber Sep 30 '22 at 12:31
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1@ OK Thank you for the link on the older question which I had not read before. – Yves Sep 30 '22 at 14:10