| Gumbel | R Documentation |
The Gumbel distribution is a special case of the \link{GEV} distribution,
obtained when the GEV shape parameter \xi is equal to 0.
It may be referred to as a type I extreme value distribution.
Gumbel(mu = 0, sigma = 1)
mu |
The location parameter, written |
sigma |
The scale parameter, written |
We recommend reading this documentation on https://alexpghayes.github.io/distributions3/, where the math will render with additional detail and much greater clarity.
In the following, let X be a Gumbel random variable with location
parameter mu = \mu, scale parameter sigma = \sigma.
Support: R, the set of all real numbers.
Mean: \mu + \sigma\gamma, where \gamma is Euler's
constant, approximately equal to 0.57722.
Median: \mu - \sigma\ln(\ln 2).
Variance: \sigma^2 \pi^2 / 6.
Probability density function (p.d.f):
f(x) = \sigma ^ {-1} \exp[-(x - \mu) / \sigma]%
\exp\{-\exp[-(x - \mu) / \sigma] \}
for x in R, the set of all real numbers.
Cumulative distribution function (c.d.f):
In the \xi = 0 (Gumbel) special case
F(x) = \exp\{-\exp[-(x - \mu) / \sigma] \}
for x in R, the set of all real numbers.
A Gumbel object.
Other continuous distributions:
Beta(),
Cauchy(),
ChiSquare(),
Erlang(),
Exponential(),
FisherF(),
Frechet(),
GEV(),
GP(),
Gamma(),
LogNormal(),
Logistic(),
Normal(),
RevWeibull(),
StudentsT(),
Tukey(),
Uniform(),
Weibull()
set.seed(27)
X <- Gumbel(1, 2)
X
random(X, 10)
pdf(X, 0.7)
log_pdf(X, 0.7)
cdf(X, 0.7)
quantile(X, 0.7)
cdf(X, quantile(X, 0.7))
quantile(X, cdf(X, 0.7))
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