| GENLOGIS | R Documentation |
GENLOGIS provides the link between L-moments of a sample and the three parameter
generalized logistic distribution.
f.genlogis (x, xi, alfa, k)
F.genlogis (x, xi, alfa, k)
invF.genlogis (F, xi, alfa, k)
Lmom.genlogis (xi, alfa, k)
par.genlogis (lambda1, lambda2, tau3)
rand.genlogis (numerosita, xi, alfa, k)
x |
vector of quantiles |
xi |
vector of genlogis location parameters |
alfa |
vector of genlogis scale parameters |
k |
vector of genlogis shape parameters |
F |
vector of probabilities |
lambda1 |
vector of sample means |
lambda2 |
vector of L-variances |
tau3 |
vector of L-CA (or L-skewness) |
numerosita |
numeric value indicating the length of the vector to be generated |
See https://en.wikipedia.org/wiki/Logistic_distribution for an introduction to the Logistic Distribution.
Definition
Parameters (3): \xi (location), \alpha (scale), k (shape).
Range of x: -\infty < x \le \xi + \alpha / k if k>0;
-\infty < x < \infty if k=0;
\xi + \alpha / k \le x < \infty if k<0.
Probability density function:
f(x) = \frac{\alpha^{-1} e^{-(1-k)y}}{(1+e^{-y})^2}
where y = -k^{-1}\log\{1 - k(x - \xi)/\alpha\} if k \ne 0,
y = (x-\xi)/\alpha if k=0.
Cumulative distribution function:
F(x) = 1/(1+e^{-y})
Quantile function:
x(F) = \xi + \alpha[1-\{(1-F)/F\}^k]/k if k \ne 0,
x(F) = \xi - \alpha \log\{(1-F)/F\} if k=0.
k=0 is the logistic distribution.
L-moments
L-moments are defined for -1<k<1.
\lambda_1 = \xi + \alpha[1/k - \pi / \sin (k \pi)]
\lambda_2 = \alpha k \pi / \sin (k \pi)
\tau_3 = -k
\tau_4 = (1+5 k^2)/6
Parameters
k=-\tau_3, \alpha = \frac{\lambda_2 \sin (k \pi)}{k \pi},
\xi = \lambda_1 - \alpha (\frac{1}{k} - \frac{\pi}{\sin (k \pi)}).
Lmom.genlogis and par.genlogis accept input as vectors of equal length. In f.genlogis, F.genlogis, invF.genlogis and rand.genlogis parameters (xi, alfa, k) must be atomic.
f.genlogis gives the density f, F.genlogis gives the distribution function F, invF.genlogis gives the quantile function x, Lmom.genlogis gives the L-moments (\lambda_1, \lambda_2, \tau_3, \tau_4), par.genlogis gives the parameters (xi, alfa, k), and rand.genlogis generates random deviates.
For information on the package and the Author, and for all the references, see nsRFA.
rnorm, runif, EXP, GENPAR, GEV, GUMBEL, KAPPA, LOGNORM, P3; DISTPLOTS, GOFmontecarlo, Lmoments.
data(hydroSIMN)
annualflows
summary(annualflows)
x <- annualflows["dato"][,]
fac <- factor(annualflows["cod"][,])
split(x,fac)
camp <- split(x,fac)$"45"
ll <- Lmoments(camp)
parameters <- par.genlogis(ll[1],ll[2],ll[4])
f.genlogis(1800,parameters$xi,parameters$alfa,parameters$k)
F.genlogis(1800,parameters$xi,parameters$alfa,parameters$k)
invF.genlogis(0.7697433,parameters$xi,parameters$alfa,parameters$k)
Lmom.genlogis(parameters$xi,parameters$alfa,parameters$k)
rand.genlogis(100,parameters$xi,parameters$alfa,parameters$k)
Rll <- regionalLmoments(x,fac); Rll
parameters <- par.genlogis(Rll[1],Rll[2],Rll[4])
Lmom.genlogis(parameters$xi,parameters$alfa,parameters$k)
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