Group Lasso Penalized Learning Using a Unified BMD Algorithm (gglasso)
A unified algorithm, blockwise-majorization-descent (BMD), for efficiently computing the solution paths of the group-lasso penalized least squares, logistic regression, Huberized SVM and squared SVM. The package is an implementation of Yang, Y. and Zou, H. (2015) DOI: <doi:10.1007/s11222-014-9498-5>.

Creates a Neighbourhood Using Locality Sensitive Hashing for Gaussian Projections (AurieLSHGaussian)
Uses locality sensitive hashing and creates a neighbourhood graph for a data set and calculates the adjusted rank index value for the same. It uses Gaussian random planes to decide the nature of a given point. Datar, Mayur, Nicole Immorlica, Piotr Indyk, and Vahab S. Mirrokni(2004) <doi:10.1145/997817.997857>.

Engle-Granger Cointegration Models (egcm)
An easy-to-use implementation of the Engle-Granger two-step procedure for identifying pairs of cointegrated series. It is geared towards the analysis of pairs of securities. Summary and plot functions are provided, and the package is able to fetch closing prices of securities from Yahoo. A variety of unit root tests are supported, and an improved unit root test is included.

Two-/Three-Stage Designs for Phase 1&2 Clinical Trials (tsdf)
Calculate optimal Zhong’s two-/three-stage Phase II designs (see Zhong (2012) <doi:10.1016/j.cct.2012.07.006>). Generate two-/three-stage dose finding decision table. This package also allows users to run dose-finding simulations based on customized decision table.

Uniform Sampling of Directed Acyclic Graphs (unifDAG)
Uniform sampling of Directed Acyclic Graphs (DAG) using exact enumeration by relating each DAG to a sequence of outpoints (nodes with no incoming edges) and then to a composition of integers as suggested by Kuipers, J. and Moffa, G. (2015) <doi:10.1007/s11222-013-9428-y>.