reversing | R Documentation |
As several Extreme Value distributions are parameterized for high extreme values, reversed functions for minima (e.g. low flow statistics) are derived. Reversing is done by fitting to the negated data (-x
), subtracting probabilities from one (1 - f
) and computing the negated probabilities.
cdf_ev(distribution, x, para) pel_ev(distribution, lmom, ...) qua_ev(distribution, f, para)
distribution |
character vector of length one containing the name of the distribution. The family of the chosen distribution must be supported by the package lmom. See |
x |
Vector of quantiles. |
f |
Vector of probabilities. |
para |
Numeric vector containing the parameters of the distribution, in the order zeta, beta, delta (location, scale, shape). |
lmom |
Numeric vector containing the L-moments of the distribution or of a data sample. E.g. as returned by |
... |
parameters like |
'cdf_ev'
gives the distribution function; 'qua_ev'
gives the quantile function.
lmom
, cdfgev
, cdfgev
, pel-functions
.
data("ngaruroro") ng <- as.xts(ngaruroro) minima <- as.vector(apply.yearly(ng$discharge, min, na.rm = TRUE)) # Weibull distribution and reversed GEV give the same results distr <- "wei" qua_ev(distr, seq(0, 1, 0.1), para = pel_ev(distr, samlmu(minima))) distr <- "gevR" qua_ev(distr, seq(0, 1, 0.1), para = pel_ev(distr, samlmu(minima)))
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.