Genetic Algorithm (GA) for Variable Selection from High-Dimensional Data (gaselect)
Provides a genetic algorithm for finding variable subsets in high dimensional data with high prediction performance. The genetic algorithm can use ordinary least squares (OLS) regression models or partial least squares (PLS) regression models to evaluate the prediction power of variable subsets. By supporting different cross-validation schemes, the user can fine-tune the tradeoff between speed and quality of the solution.

C++ Header Files for Stan (StanHeaders)
The C++ header files associated with the Stan project. Stan is a probabilistic programming language implementing full Bayesian statistical inference with MCMC sampling and penalized maximum likelihood estimation with optimization. See <http://mc-stan.org/> for more information.

Cone Constrained Convex Problems (cccp)
Routines for solving convex optimization problems with cone constraints by means of interior-point methods. The implemented algorithms are partially ported from CVXOPT, a Python module for convex optimization (see <http://cvxopt.org> for more information).

Sparse Group Partial Least Square Methods (sgPLS)
The Sparse Group Partial Least Square package (sgPLS) provides sparse, group, and sparse group versions of partial least square regression models.

R Interface to the Pushbullet Messaging Service (RPushbullet)
An R interface to the Pushbullet messaging service which provides fast and efficient notifications (and file transfer) between computers, phones and tablets. An account has to be registered at the site http://www.pushbullet.com site to obtain a (free) API key.

Linked Micromap Plots (micromap)
This group of functions simplifies the creation of linked micromap plots.

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