evfit: Fit an extreme value distribution to observations
In lfstat: Calculation of Low Flow Statistics for Daily Stream Flow Data

Description Usage Arguments Details Value See Also Examples

Fits an extreme value distribution using L-moments to the values provided. In the presence of zero flow observations a mixed distribution is fitted.

1 2	evfit(x, distribution, zeta = NULL, check = TRUE, extreme = c("minimum", "maximum"))

`x`	numeric vector. Data which is an extreme value distribution is fitted to.
`distribution`	A character vector of distributions to fit. Basically all distributions provided by Hosking's `lmom-package` and their reversed counterparts can be chosen. See `reversing`.
`zeta`	numeric vector of length one for manually setting a lower bound. Only a few distributions allow for a lower bound, namely `'gpa'`, `'ln3'`, `'wak'` and `'wei'`. The default value of `NULL` results in not bounding the distribution, therefore the parameter `zeta` is estimated.
`check`	logical, should `check_distribution` get called?
`extreme`	character vector of length one. Can be either `'minimum'` or `'maximum'`. Helps to choose a correct distribution.

This function is vectorized over distribution.

According to paragraph 7.4.2 of the WMO manual, special care has to be taken in the presence of zero flow observations. A cdf called G(x) is fitted to the non-zero values of the original time series.

If a distribution is fitted which allows for finite lower bound (zeta), and zeta is estimated being negative, estimation is repeated constraining zeta = 0. If this behavior is not desired, the parameter zeta has to be set explicitly.

An object of class evfit containing the L-moments and the estimated parameters is returned. Objects of class evfit are basically a list with the following elements:

`values`	the values `x` used for fitting.
`freq.zeros`	a character vector of length one. Frequency of zero flow observations.
`is.censored`	logical, if the censored time was used for fitting.
`parameters`	a list as long as `distribution` containing the estimated parameters for each distribution.
`lmom`	sample L-moments of the censored series (only containing non-zero values).
`extreme`	character vector of length one, indicating what kind of extreme value was fitted.
`T_Years_Event`	optional. If quantiles have been computed they a stored in a matrix with return periods in rows and distributions in columns.

There are methods for printing summarizing objects of class evfit.

evfit

data("ngaruroro")
ng <- as.xts(ngaruroro)
minima <- as.vector(apply.yearly(ng$discharge, min, na.rm = TRUE))
evfit(x = minima, distribution = c("wei", "gevR"),
      extreme = "minimum")

Loading required package: xts
Loading required package: zoo

Attaching package: 'zoo'

The following objects are masked from 'package:base':

    as.Date, as.Date.numeric

Loading required package: lmom
Loading required package: lattice
Values: num [1:38] 4.97 3.34 4.8 5.02 4.82 ...


L-Moments:
       l_1        l_2        t_3        t_4 
4.11100000 0.48256188 0.04225708 0.13378016 

Fitted Parameters of the Distribution:
wei    zeta:   1.93213,  beta:   2.44796,  delta:  2.76869
gevR   xi:    -4.38009,  alpha: 0.884158,  k:     0.361181
Warning message:
For fitting minima, a Weibull distribution with parameter 'zeta = 0' may be best.