extremeStat: Extreme value statistics on a linear scale

In brry/extremeStat: Extreme Value Statistics and Quantile Estimation

Extreme value statistics on a linear scale

Description

Fit (via L moments), plot (on a linear scale) and compare (by goodness of fit) several (extreme value) distributions. Compute high quantiles even in small samples and estimate extrema at given return periods.
Open the Vignette for an introduction to the package: vignette("extremeStat")
This package heavily relies on and thankfully acknowledges the package lmomco by WH Asquith.

Package overview

The main functions in the extremeStat package are:

distLweights	-> plotLweights
distLfit	-> plotLfit
q_gpd + q_weighted -> distLquantile	-> plotLquantile
distLextreme	-> plotLextreme
distLexBoot

They create and modify a list object printed by (and documented in) printL.

Author(s)

Berry Boessenkool, [e-mail], 2014-2016

See Also

If you are looking for more detailed (uncertainty) analysis, eg confidence intervals, check out the package extRemes, especially the function fevd. https://cran.r-project.org/package=extRemes
Intro slides: https://sites.lsa.umich.edu/eva2015/wp-content/uploads/sites/44/2015/06/Intro2EVT.pdf
Parameter fitting and distribution functions: https://cran.r-project.org/package=lmomco
Distributions: https://web.archive.org/web/20110807225801/https://www.rmetrics.org/files/Meielisalp2009/Presentations/Scott.pdf and: https://cran.r-project.org/view=Distributions
R in Hydrology: https://abouthydrology.blogspot.de/2012/08/r-resources-for-hydrologists.html

Examples

data(annMax) # annual discharge maxima from a stream in Austria
plot(annMax, type="l")
dle <- distLextreme(annMax)
dle$returnlev

brry/extremeStat documentation built on Feb. 2, 2024, 2:06 a.m.