Keywords: Data depth, Supervised classification, DD-plot, Outsiders, Visualization
Webpages:
https://cran.r-project.org/package=ddalpha Following the seminal idea of John W. Tukey, data depth is a function that measures how close an arbitrary point of the space is located to an implicitly defined center of a data cloud. Having undergone theoretical and computational developments, it is now employed in numerous applications with classification being the most popular one. The
R-package
ddalpha is a software directed to fuse experience of the applicant with recent achievements in the area of data depth and depth-based classification.
ddalpha provides an implementation for exact and approximate computation of most reasonable and widely applied notions of data depth. These can be further used in the depth-based multivariate and functional classifiers implemented in the package, where the \(DD\alpha\)-procedure is in the main focus. The package is expandable with user-defined custom depth methods and separators. The implemented functions for depth visualization and the built-in benchmark procedures may also serve to provide insights into the geometry of the data and the quality of pattern recognition.
