Other packages

Stephen Chan Manchester University

Other packages for extreme value analysis presented in this page have been proposed by Stephen Chan (University of Manchester).

GUI package: Xtremes 3.0

Description: A professional version of the package, which allows for large datasets to be analyzed, is available for purchase at Xtremes represents a fairly complete analysis package aimed primarily at finance and hydrology applications, but the methods are generally applicable.

GUI software package written in C++: EXTREMES 2.0

Description: The EXTREMES software gathers different tools dedicated to extreme values study. More precisely, it focuses on extreme quantiles estimation and model selection for distribution tails. It is written in C++ with a graphical user interface developped with the library QT. This solution matches rapid execution and user-friendliness.

Commercial standalone software products: HYFRAN and HYFRAN-PLUS (HYdrological FRequency ANalysis)

Authors: Group of researchers at INRS University, Canada
Description: is a software used to fit statistical distributions. It includes a number of powerful, flexible, user-friendly mathematical tools that can be used for the statistical analysis of extreme events. It can also, more generally, perform basic analysis of any time series of Independent and Indentically Distributed (IID) data.

S-Plus Software: S+FinMetrics 2.0

Authors: Andrew Bruce, Doug Martin, Jiahui Wang, Eric Zivot and developed by Insightful Corporation.
Description: Provides advanced analytic-rich software for modeling, analyzing, and visualizing financial market data. The software offers the most comprehensive, modern, and flexible analytic tool available for precise, predictive econometric modeling of financial time series.

Fortran: GLSNet

Version: 2.6
Description: Performs prediction of low/high flows at non-instrumented locations using regression techniques and generalized least squares.

Fortran: peakFQ

Version: 7.1
Description: Estimates annual peak flows for several return periods by fitting a Pearson Type III distribution, i.e., a Gamma distribution, using the logarithmic sample moments.

Stephen Chan Manchester University

Stephen Chan

University of Manchester