The goal of 'Momocs' is to provide a complete, convenient, 
       reproducible and open-source toolkit for 2D morphometrics.
       It includes most common 2D morphometrics approaches on outlines, open outlines, 
       configurations of landmarks, traditional morphometrics, and facilities for data preparation, 
       manipulation and visualization with a consistent grammar throughout.
       It allows reproducible, complex morphometrics analyses and other morphometrics approaches 
       should be easy to plug in, or develop from, on top of this canvas. Companion paper is published 
       in JSS Bonhomme V, Picq S, Gaucherel C and Claude J (2014) <doi:10.18637/jss.v056.i13>. 
       Now superseded by 'Momocs2' and the 'MomX' ecosystem.
       'Momocs' should be considered retired and will no longer be supported someday.

It computes arbitrary products moments (mean vector and variance-covariance matrix), for some double truncated (and folded) multivariate distributions. These distributions belong to the family of selection elliptical distributions, which includes well known skewed distributions as the unified skew-t distribution (SUT) and its particular cases as the extended skew-t (EST), skew-t (ST) and the symmetric student-t (T) distribution. Analogous normal cases unified skew-normal (SUN), extended skew-normal (ESN), skew-normal (SN), and symmetric normal (N) are also included. Density, probabilities and random deviates are also offered for these members.

A HTML widget rendering the 'Monaco' editor. The 'Monaco' editor is the code editor which powers 'VS Code'. It is particularly well developed for 'JavaScript'. In addition to the built-in features of the 'Monaco' editor, the widget allows to prettify multiple languages, to view the 'HTML' rendering of 'Markdown' code, and to view and resize 'SVG' images.

Compose generic monadic function pipelines with %>>% and %>-%
    based on implementing the 'S7' generics fmap() and bind(). Methods are
    provided for the built-in list type and the maybe class from the
    'maybe' package. The concepts are modelled directly after the Monad
    typeclass in Haskell, but adapted for idiomatic use in R.