Enforces good practice and provides convenience functions to make work with 'JavaScript' 
  not just easier but also scalable. It is a robust wrapper to 'NPM', 'yarn', and 'webpack' that 
  enables to compartmentalize 'JavaScript' code, leverage 'NPM' and 'yarn' packages, include
  'TypeScript', 'React', or 'Vue' in web applications, and much more.

Various useful functions for statisticians: describe data, plot Kaplan-Meier curves with numbers of subjects at risk, compare data sets, display spaghetti-plot, build multi-contingency tables...

Several functions are provided to implement a MBPLSDA : components search, optimal model components number search, optimal model validity test by permutation tests, observed values evaluation of optimal model parameters and predicted categories, bootstrap values evaluation of optimal model parameters and predicted cross-validated categories. The use of this package is described in Brandolini-Bunlon et al (2019. Multi-block PLS discriminant analysis for the joint analysis of metabolomic and epidemiological data. Metabolomics, 15(10):134).

Manage the R packages your project depends on in an isolated,
    portable, and reproducible way.

An implementation of both the equality and inequality constrained lasso
    functions for the algorithm described in "Penalized and Constrained Optimization"
    by James, Paulson, and Rusmevichientong (Journal of the American Statistical Association, 2019;
    see <http://www-bcf.usc.edu/~gareth/research/PAC.pdf> for a full-text version of the paper). 
    The algorithm here is designed to allow users to define linear constraints (either equality
    or inequality constraints) and use a penalized regression approach to solve the constrained
    problem. The functions here are used specifically for constraints with the lasso formulation,
    but the method described in the PaC paper can be used for a variety of scenarios. In addition
    to the simple examples included here with the corresponding functions, complete code to 
    entirely reproduce the results of the paper is available online through the Journal of the
    American Statistical Association.