GUMBEL {nsRFA} | R Documentation |
Two parameter Gumbel distribution and L-moments
Description
GUMBEL
provides the link between L-moments of a sample and the two parameter
Gumbel distribution.
Usage
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)
Arguments
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 |
Details
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.
Value
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.
Note
For information on the package and the Author, and for all the references, see nsRFA
.
See Also
rnorm
, runif
, EXP
, GENLOGIS
, GENPAR
, GEV
, KAPPA
, LOGNORM
, P3
; DISTPLOTS
, GOFmontecarlo
, Lmoments
.
Examples
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)