MLlaio2004 {nsRFA} | R Documentation |
Maximum Likelihood estimation of parameters for extreme-value distributions, from Laio (2004).
ML_estimation (x, dist="NORM") moment_estimation (x, dist="NORM") logLgumb (T, x) logLgev (T, x) logLgam (T1, x) sample_generator (n, T, dist="NORM")
x |
data sample |
dist |
distribution: normal "NORM" , Gumbel "EV1" , Generalized Extreme Value "GEV" , Pearson type III "GAM" and, only for sample_generator , Exponential EXP |
T |
parameters (position, scale, shape, ...) |
T1 |
position parameter of the Gamma (Pearson type III) distribution |
n |
sample length |
ML_estimation
estimate the parameters of the distribution dist
from a sample x
using the maximum likelihood approach.
moment_estimation
estimate the parameters of the distribution dist
from a sample x
using the moment method.
logLgumb
is the negative log-likelihood function for the Gumbel distribution.
logLgev
is the negative log-likelihood function for the Generalized Extreme Value distribution.
logLgam
is the negative log-likelihood function for the Pearson type III distribution.
sample_generator
generates a sample of length n
from the distribution dist
with parameters T
.
Alberto Viglione, e-mail: alviglio@tiscali.it.
Laio, F., Cramer-von Mises and Anderson-Darling goodness of fit tests for extreme value distributions with unknown parameters, Water Resour. Res., 40, W09308, doi:10.1029/2004WR003204.
sm <- sample_generator(100, c(0,1), dist="EV1") moment_estimation (sm, dist="GEV") ML_estimation (sm, dist="GEV") Fx (sm, c(-0.051,0.97,-0.024), dist="GEV") sample_generator (100, c(-0.051,0.97,-0.024), dist="GEV") moment_estimation (sm, dist="GAM") ML_estimation (sm, dist="GAM") Fx (sm, c(-1.6,0.78,2.8), dist="GAM")