We recommend reading this documentation on pkgdown which renders math nicely.
https://pkg.mitchelloharawild.com/distributional/reference/dist_gumbel.html
In the following, let \(X\) be a Gumbel random variable with location
parameter alpha = \(\alpha\) and scale parameter scale = \(\sigma\).
Support: \(R\), the set of all real numbers.
Mean:
$$
E(X) = \alpha + \sigma\gamma
$$
where \(\gamma\) is the Euler-Mascheroni constant,
approximately equal to 0.5772157.
Variance:
$$
\textrm{Var}(X) = \frac{\pi^2 \sigma^2}{6}
$$
Skewness:
$$
\textrm{Skew}(X) = \frac{12\sqrt{6}\zeta(3)}{\pi^3} \approx 1.1395
$$
where \(\zeta(3)\) is Apery's constant,
approximately equal to 1.2020569. Note that skewness is independent
of the distribution parameters.
Kurtosis (excess):
$$
\textrm{Kurt}(X) = \frac{12}{5} = 2.4
$$
Note that excess kurtosis is independent of the distribution parameters.
Median:
$$
\textrm{Median}(X) = \alpha - \sigma\ln(\ln 2)
$$
Probability density function (p.d.f):
$$
f(x) = \frac{1}{\sigma} \exp\left[-\frac{x - \alpha}{\sigma}\right]
\exp\left\{-\exp\left[-\frac{x - \alpha}{\sigma}\right]\right\}
$$
for \(x\) in \(R\), the set of all real numbers.
Cumulative distribution function (c.d.f):
$$
F(x) = \exp\left\{-\exp\left[-\frac{x - \alpha}{\sigma}\right]\right\}
$$
for \(x\) in \(R\), the set of all real numbers.
Quantile function (inverse c.d.f):
$$
F^{-1}(p) = \alpha - \sigma \ln(-\ln p)
$$
for \(p\) in (0, 1).
Moment generating function (m.g.f):
$$
E(e^{tX}) = \Gamma(1 - \sigma t) e^{\alpha t}
$$
for \(\sigma t < 1\), where \(\Gamma\) is the gamma function.