Heuristics Tools Based on Mutual Information for Variable Ranking (varrank)
A computational toolbox of heuristics approaches for performing variable ranking and feature selection based on mutual information well adapted for multivariate system epidemiology datasets. The core function is a general implementation of the minimum redundancy maximum relevance model. R. Battiti (1994) <doi:10.1109/72.298224>. Continuous variables are discretized using a large choice of rule. Variables ranking can be learned with a sequential forward/backward search algorithm. The two main problems that can be addressed by this package is the selection of the most representative variable within a group of variables of interest (i.e. dimension reduction) and variable ranking with respect to a set of features of interest.

The Expectation-Maximization Approach to Bayesian Variable Selection (EMVS)
An efficient expectation-maximization algorithm for fitting Bayesian spike-and-slab regularization paths for linear regression. Rockova and George (2014) <doi:10.1080/01621459.2013.869223>.

Determine a Script’s Filename from Within the Script Itself (scriptName)
A small set of functions wrapping up the call stack and command line inspection needed to determine a running script’s filename from within the script itself.

Finds the Best Subset of Points to Sample (NITPicker)
Given a few examples of experiments over a time (or spatial) course, ‘NITPicker’ selects a subset of points to sample in follow-up experiments, which would (i) best distinguish between the experimental conditions and the control condition (ii) best distinguish between two models of how the experimental condition might differ from the control (iii) a combination of the two. Ezer and Keir (2018) <doi:10.1101/301796>.

Visualizing Social Science Data with ‘ggplot2’ (ggpol)
A ‘ggplot2’ extension for implementing parliament charts and several other useful visualizations.