Parameters |
(
real) shape (real) | ||
---|---|---|---|
CDF | |||
Mean | |||
Variance |
In probability theory, the Type-2 Gumbel probability density function is
for
For the mean is infinite. For the variance is infinite.
The cumulative distribution function is
The moments exist for
The distribution is named after Emil Julius Gumbel (1891 – 1966).
Given a random variate U drawn from the uniform distribution in the interval (0, 1), then the variate
has a Type-2 Gumbel distribution with parameter and . This is obtained by applying the inverse transform sampling-method.
Based on The GNU Scientific Library, used under GFDL.
Parameters |
(
real) shape (real) | ||
---|---|---|---|
CDF | |||
Mean | |||
Variance |
In probability theory, the Type-2 Gumbel probability density function is
for
For the mean is infinite. For the variance is infinite.
The cumulative distribution function is
The moments exist for
The distribution is named after Emil Julius Gumbel (1891 – 1966).
Given a random variate U drawn from the uniform distribution in the interval (0, 1), then the variate
has a Type-2 Gumbel distribution with parameter and . This is obtained by applying the inverse transform sampling-method.
Based on The GNU Scientific Library, used under GFDL.