Estimate the mean of a Gaussian vector, by choosing among a large collection of estimators,
  following the method developed by Y. Baraud, C. Giraud and S. Huet (2014) <doi:10.1214/13-AIHP539>.
  In particular it solves the problem of variable selection by choosing the best predictor among predictors emanating from different methods as lasso,
  elastic-net, adaptive lasso, pls, randomForest. Moreover, it can be applied for choosing the tuning parameter in a Gauss-lasso procedure.

Variable elimination (Gaussian elimination, Fourier-Motzkin elimination), 
    Moore-Penrose pseudoinverse, reduction to reduced row echelon form, value substitution,  
    projecting a vector on the convex polytope described by a system of (in)equations, 
    simplify systems by removing spurious columns and rows and collapse implied equalities, 
    test if a matrix is totally unimodular, compute variable ranges implied by linear
    (in)equalities.

Checks adherence to a given style, syntax errors and possible
    semantic issues.  Supports on the fly checking of R code edited with
    'RStudio IDE', 'Emacs', 'Vim', 'Sublime Text', 'Atom' and 'Visual
    Studio Code'.

Extends the functionality of the 'tourr' package by an interactive
             graphical user interface. The interactivity allows users to
             effortlessly refine their 'tourr' results by manual intervention,
             which allows for integration of expert knowledge and aids the
             interpretation of results. For more information on 'tourr' see
             Wickham et. al (2011) <doi:10.18637/jss.v040.i02> or
             <https://github.com/ggobi/tourr>.

Lipid Maps Rest service. Researchers can access the Lipid Maps Rest
  service programmatically and conveniently integrate it into the current workflow
  or packages.

Lipid annotation in untargeted LC-MS lipidomics based on fragmentation rules. Alcoriza-Balaguer MI, Garcia-Canaveras JC, Lopez A, Conde I, Juan O, Carretero J, Lahoz A (2019) <doi:10.1021/acs.analchem.8b03409>.