Outlier Detection Algorithms for High-Dimensional Data (HighDimOut)
Three high-dimensional outlier detection algorithms and a outlier unification scheme are implemented in this package. The angle-based outlier detection (ABOD) algorithm is based on the work of Kriegel, Schubert, and Zimek . The subspace outlier detection (SOD) algorithm is based on the work of Kriegel, Kroger, Schubert, and Zimek . The feature bagging-based outlier detection (FBOD) algorithm is based on the work of Lazarevic and Kumar . The outlier unification scheme is based on the work of Kriegel, Kroger, Schubert, and Zimek .
R interface to matplotlib (Rpyplot)
R interface to matplotlib via Rcpp using Python 2.7 or 3. Contains basic working interface to some basic with few options. Tested with Ubuntu 14.10 (System Python 2.7, 3.4) and Windows 7 (Anaconda Python 2.7, 3.4). Why? I often use Python and matplotlib for exploring measurement data (from e.g. accelerometers), even if I use R for the actual analysis. The reason is that I like to be able to flexibly zoom into different parts of the plot using the mouse and this works well for me with matplotlib. So I decided to try to call matplotlib from R using Rcpp and Python/C API. It was surprisingly simple to get it working so I put together this package.
Tools for Inference with Set-Theoretic Comparative Methods (stcm)
Provides a number of functions for carrying out inference with set-theoretic comparative methods, including facilities for examining causal paths, assessing the sensitivity of results to measurement and model specification error, and performing Random Forest Comparative Analysis.