Probability distribution
Type-2 Gumbel Parameters a ∈ R {\displaystyle \ a\in \mathbb {R} \ } (shape), b ∈ R {\displaystyle \ b\in \mathbb {R} \ } (scale) Support 0 < x < ∞ {\displaystyle \ 0<x<\infty \ } PDF a b x − a − 1 e − b x − a {\displaystyle \ a\ b\ x^{-a-1}\ e^{-b\ x^{-a}}\ } CDF e − b x − a {\displaystyle \ e^{-b\ x^{-a}}\ } Quantile ( − log e ( p ) b ) − 1 a {\displaystyle \ \left(-\ {\frac {\ \log _{e}\!\left(p\right)\ }{b}}\right)^{-{\frac {1}{a}}}\ } Mean b 1 a Γ ( 1 − 1 a ) {\displaystyle \ b^{\frac {1}{a}}\ \Gamma \!\left(\ 1-{\tfrac {\ 1\ }{a}}\ \right)\ } Variance b 2 a Γ ( 1 − 1 a ) ( 1 − Γ ( 1 − 1 a ) ) {\displaystyle \ b^{\frac {2}{a}}\ \Gamma \!\left(1-{\tfrac {\ 1\ }{a}}\ \right){\Bigl (}1-\Gamma \!\left(1-{\tfrac {1}{a}}\right){\Bigr )}\ }
In probability theory , the Type-2 Gumbel probability density function is
f ( x | a , b ) = a b x − a − 1 e − b x − a {\displaystyle \ f(x|a,b)=a\ b\ x^{-a-1}\ e^{-b\ x^{-a}}\quad } for x > 0 . {\displaystyle \quad x>0~.} For 0 < a ≤ 1 {\displaystyle \ 0<a\leq 1\ } the mean is infinite. For 0 < a ≤ 2 {\displaystyle \ 0<a\leq 2\ } the variance is infinite.
The cumulative distribution function is
F ( x | a , b ) = e − b x − a . {\displaystyle \ F(x|a,b)=e^{-b\ x^{-a}}~.} The moments E [ X k ] {\displaystyle \ \mathbb {E} {\bigl [}X^{k}{\bigr ]}\ } exist for k < a {\displaystyle \ k<a\ }
The distribution is named after Emil Julius Gumbel (1891 – 1966).
Generating random variates [ edit ] Given a random variate U {\displaystyle \ U\ } drawn from the uniform distribution in the interval ( 0 , 1 ) , {\displaystyle \ (0,1)\ ,} then the variate
X = ( − ln U b ) − 1 a {\displaystyle X=\left(-{\frac {\ln U}{b}}\right)^{-{\frac {1}{a}}}\ } has a Type-2 Gumbel distribution with parameter a {\displaystyle \ a\ } and b . {\displaystyle \ b~.} This is obtained by applying the inverse transform sampling -method.
Substituting b = λ − k {\displaystyle \ b=\lambda ^{-k}\ } and a = − k {\displaystyle \ a=-k\ } yields the Weibull distribution . Note, however, that a positive k {\displaystyle \ k\ } (as in the Weibull distribution) would yield a negative a {\displaystyle \ a\ } and hence a negative probability density, which is not allowed. Based on "Gumbel distribution" . The GNU Scientific Library . type 002d2, used under GFDL.
Discrete univariate
with finite support with infinite support
Continuous univariate
supported on a bounded interval supported on a semi-infinite interval supported on the whole real line with support whose type varies
Mixed univariate
Multivariate (joint) Directional Degenerate and singular Families