| GUMBEL | R Documentation |
GUMBEL provides the link between L-moments of a sample and the two parameter
Gumbel distribution.
f.gumb (x, xi, alfa)
F.gumb (x, xi, alfa)
invF.gumb (F, xi, alfa)
Lmom.gumb (xi, alfa)
par.gumb (lambda1, lambda2)
rand.gumb (numerosita, xi, alfa)
x |
vector of quantiles |
xi |
vector of gumb location parameters |
alfa |
vector of gumb scale parameters |
F |
vector of probabilities |
lambda1 |
vector of sample means |
lambda2 |
vector of L-variances |
numerosita |
numeric value indicating the length of the vector to be generated |
See https://en.wikipedia.org/wiki/Fisher-Tippett_distribution for an introduction to the Gumbel distribution.
Definition
Parameters (2): \xi (location), \alpha (scale).
Range of x: -\infty < x < \infty.
Probability density function:
f(x) = \alpha^{-1} \exp[-(x-\xi)/\alpha] \exp\{- \exp[-(x-\xi)/\alpha]\}
Cumulative distribution function:
F(x) = \exp[-\exp(-(x-\xi)/\alpha)]
Quantile function:
x(F) = \xi - \alpha \log(-\log F).
L-moments
\lambda_1 = \xi + \alpha \gamma
\lambda_2 = \alpha \log 2
\tau_3 = 0.1699 = \log(9/8)/ \log 2
\tau_4 = 0.1504 = (16 \log 2 - 10 \log 3)/ \log 2
Here \gamma is Euler's constant, 0.5772...
Parameters
\alpha=\lambda_2 / \log 2
\xi = \lambda_1 - \gamma \alpha
Lmom.gumb and par.gumb accept input as vectors of equal length. In f.gumb, F.gumb, invF.gumb and rand.gumb parameters (xi, alfa) must be atomic.
f.gumb gives the density f, F.gumb gives the distribution function F, invF.gumb gives
the quantile function x, Lmom.gumb gives the L-moments (\lambda_1, \lambda_2, \tau_3, \tau_4)), par.gumb gives the parameters (xi, alfa), and rand.gumb generates random deviates.
For information on the package and the Author, and for all the references, see nsRFA.
rnorm, runif, EXP, GENLOGIS, GENPAR, GEV, KAPPA, LOGNORM, P3; DISTPLOTS, GOFmontecarlo, Lmoments.
data(hydroSIMN)
annualflows[1:10,]
summary(annualflows)
x <- annualflows["dato"][,]
fac <- factor(annualflows["cod"][,])
split(x,fac)
camp <- split(x,fac)$"45"
ll <- Lmoments(camp)
parameters <- par.gumb(ll[1],ll[2])
f.gumb(1800,parameters$xi,parameters$alfa)
F.gumb(1800,parameters$xi,parameters$alfa)
invF.gumb(0.7686843,parameters$xi,parameters$alfa)
Lmom.gumb(parameters$xi,parameters$alfa)
rand.gumb(100,parameters$xi,parameters$alfa)
Rll <- regionalLmoments(x,fac); Rll
parameters <- par.gumb(Rll[1],Rll[2])
Lmom.gumb(parameters$xi,parameters$alfa)
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