A software review for extreme value analysis

Abstract

Extreme value methodology is being increasingly used by practitioners from a wide range of fields. The importance of accurately modeling extreme events has intensified, particularly in environmental science where such events can be seen as a barometer for climate change. These analyses require tools that must be simple to use, but must also implement complex statistical models and produce resulting inferences. This document presents a review of the software that is currently available to scientists for the statistical modeling of extreme events. We discuss all software known to the authors, both proprietary and open source, targeting different data types and application areas. It is our intention that this article will simplify the process of understanding the available software, and will help promote the methodology to an expansive set of scientific disciplines.

Magnitude and frequency of heat and cold waves in recent decades: the case of South America

“…The code used to produce Bogota's daily temperature graphic has been provided by http://rpubs.com/bradleyboehmke/weather_graphic. Heat and cold wave magnitude indices have been computed using the R library "extRemes" (Gilleland, 2015). Google data are registered trademarks of Google Inc., used with permission.…”

The impact of ENSO and the NAO on extreme winter precipitation in North America in observations and regional climate models

“…All analysis is conducted in the R Statistical Computing environment (R Development Core Team 2014) and the GEV analysis uses the 'extRemes' package (Gilleland 2014). …”

Modelling of Extreme maximum Rainfall using Extreme Value Theory for Tanzania

“…In this study, we fit and compare the performance of two different distributions GEV and GPD distributions. We used the R Package for extremes (Gilleland et al, 2013) that is able to perform parametric inf er ent ia l analysis of the GEV and GPD distributions for each station.…”