In this section R-code related to the ICSH topics will be collected.
The Coordinator of this initiative is Martinus van den Berg (ICSH member from Ghent University)
Feel free to suggest to the Coordinator the codes you think are useful for statistical hydrological application.
Section the code should be in (any of the topics)
Name of the Package.
License terms (e.g. MIT license, free software, GPL).
A small text that describes the package.
Details for citation, if any.
Whether it is a collection of code or a package.
If it already has been published, and if so a link to the location of this repository.
List of Codes
I update on August 2012 by Martinus van den Berg
II update on May 2013 by Martinus van den Berg
copula: Multivariate Dependence with Copulas
Authors: Marius Hofert, Ivan Kojadinovic, Martin Maechler, and Jun Yan
License: GPL 3
Description: Classes (S4) of commonly used elliptical, Archimedean, extreme value and some more copula families. Methods for density, distribution, random number generation, bivariate dependence measures, perspective and contour plots. Fitting copula models including variance estimates. Independence and serial (univariate and multivariate) independence tests, and other copula related tests. Goodness-of-fit tests for copulas based on multipliers, the parametric bootstrap with several transformation options. Merged former package 'nacopula' for nested Archimedean copulas: Efficient sampling algorithms, various estimators, goodness-of-fit tests and related tools and special functions.
Instructions: Install the package by typing install.packages("copula") or download the package here.
spcopula: (spatial) Vine copulas for multivariate dependence
Authors: Benedikt Graler
License: GPL 3
Description: The spcopula package provides functions based on multivariate copulas (e.g. vine copulas) to calculate multivariate joint return periods for a set of variables. These include the joint return period of the or-case where either one of the margins may be larger than the design event and the joint Kendall return period being consistent with the univariate concept of classifying all possible events through their cumulative distribution function. Some copula families allow for joint tail dependence and are powerful tools in the multivariate extreme value analysis. Additional functions using the concept of spatial vine copulas are provided to model spatial multivariate distributions. Copula families may change over space allowing not only for a varying strength of dependence but for changing dependence structures. These distributions can then for instance be used to predict values at unobserved locations or do risk assessment.
Instructions: The package can be found here
rtop: Interpolation of data with variable spatial support
Authors: Jon Olav Skoien
License: GPL (>= 2)
Description:Package for geostatistical interpolation of data with irregular spatial support such as runoff related data or data from administrative units.
Instructions: The package can be installed as install.packages("rtop"), or find it here.