RoCoCo - An R Package Implementing a Robust Rank Correlation Coefficient and a Corresponding Test
This is a legacy page. The package is now hosted on GitHub.
Classical rank correlation measures are designed for ordinal data, but they are not ideally suited for measuring rank correlation for numerical data that are perturbed by noise. We introduced a family of robust rank correlation measures on the basis of Goodman's and Kruskal's gamma, where the classical ordering of real numbers is replaced by some fuzzy ordering with smooth transitions - thereby ensuring that the correlation measure is continuous with respect to the data. The present R package implements this rank correlation measure along with a corresponding statistical test. Moreover, the package also implements the Gaussian rank correlation estimator and a corresponding statistical test.Installation
The package is available through CRAN - The Comprehensive R Archive Network (click here to view the archive entry of the package). Therefore, the simplest way to install the package is to enter
install.packages("rococo")
into your R session. If, for what reason ever, you prefer to install the package manually, follow the instructions in the user manual.
User support
If you encounter any issues or if you have any question that might be of interest also for other users, before writing a private message to the package developers/maintainers, please create an issue in the source code repository and also consider posting on to the R-help Mailing List or on StackOverflow.Citing this package
If you use this package for research that is published later, you are kindly asked to cite it as follows:U. Bodenhofer, M. Krone, and F. Klawonn (2013). Testing noisy numerical data for monotonic association. Inform. Sci. 245:21-37. DOI: 10.1016/j.ins.2012.11.026.
U. Bodenhofer and F. Klawonn (2008). Robust rank correlation coefficients on the basis of fuzzy orderings: initial steps. Mathware Soft Comput. 15(1):5-20.