Causal Additive Model (CAM) (CAM)
The code takes an n x p data matrix and fits a Causal Additive Model (CAM) for estimating the causal structure of the underlying process. The output is a p x p adjacency matrix (a one in entry (i,j) indicates an edge from i to j). Details of the algorithm can be found in: P. Bühlmann, J. Peters, J. Ernest: “CAM: Causal Additive Models, high-dimensional order search and penalized regression”, Annals of Statistics 42:2526-2556, 2014.

Binarization of One-Dimensional Data (Binarize)
Provides methods for the binarization of one-dimensional data and some visualization functions.

Bi-Directional Interface Between R and Scala with Callbacks (rscala)
The Scala interpreter is embedded in R and callbacks to R from the embedded interpreter are supported. Conversely, the R interpreter is embedded in Scala. Scala versions 2.10 and 2.11 are supported.