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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