Momocs: Momocs

Description Details Cheers References See Also


A complete toolkit for morphometrics, from data extraction to multivariate analyses. Most common 2D morphometrics approaches are included: outlines, open outlines, configurations of landmarks, traditional morphometrics, and facilities for data preparation, manipulation and visualization with a consistent grammar throughout. Momocs allows reproducible, complex morphometric analyses, paves the way for a pure open-source workflow in R, and other morphometrics approaches should be easy to plug in, or develop from, on top of this canvas.


To cite Momocs in publications: citation("Momocs").


We are very grateful to (in alphabetical order): Sean Asselin, Laurent Bouby, Matt Bulbert, Simon Crameri, Julia Cooke, April Dinwiddie, Carl Lipo, Cedric Gaucherel, Catherine Girard, Sarah Ivorra, Glynis Jones, Nathalie Keller, Ricardo Kriebel, Remi Laffont, Fabien Lafuma, Stas Malavin, Neus Martinez, Sabrina Renaud, Marcelo Reginato, Evan Saitta, David Siddons, Eleanor Stillman, Theodore Stammer, Norbert Telmon, Jean-Frederic Terral, Bill Venables, Daniele Ventura, Michael Wallace, Asher Wishkerman, John Wood for their helpful ideas and bug reports.


See Also

Momocs documentation built on Sept. 28, 2017, 9:04 a.m.