Parallel Runs of Reverse Depends (prrd)
Reverse depends for a given package are queued such that multiple workers can run the tests in parallel.

Critical Line Algorithm in Pure R (CLA)
Implements ‘Markovitz’ Critical Line Algorithm (‘CLA’) for classical mean-variance portfolio optimization. Care has been taken for correctness in light of previous buggy implementations.

Extension for ‘R6’ Base Class (r6extended)
Useful methods and data fields to extend the bare bones ‘R6’ class provided by the ‘R6’ package – ls-method, hashes, warning- and message-method, general get-method and a debug-method that assigns self and private to the global environment.

Run Predictions Inside the Database (tidypredict)
It parses a fitted ‘R’ model object, and returns a formula in ‘Tidy Eval’ code that calculates the predictions. It works with several databases back-ends because it leverages ‘dplyr’ and ‘dbplyr’ for the final ‘SQL’ translation of the algorithm. It currently supports lm(), glm() and randomForest() models.

Bayesian Structure Learning in Graphical Models using Birth-Death MCMC (BDgraph)
Provides statistical tools for Bayesian structure learning in undirected graphical models for continuous, discrete, and mixed data. The package is implemented the recent improvements in the Bayesian graphical models literature, including Mohammadi and Wit (2015) <doi:10.1214/14-BA889> and Mohammadi et al. (2017) <doi:10.1111/rssc.12171>. To speed up the computations, the BDMCMC sampling algorithms are implemented in parallel using OpenMP in C++.