Multivariate Morphometric Analysis

Tools for multivariate analyses of morphological data, wrapped in one package, to make the workflow convenient and fast. Statistical and graphical tools provide a comprehensive framework for checking and manipulating input data, statistical analyses, and visualization of results. Several methods are provided for the analysis of raw data, to make the dataset ready for downstream analyses. Integrated statistical methods include hierarchical classification, principal component analysis, principal coordinates analysis, non-metric multidimensional scaling, and multiple discriminant analyses: canonical, stepwise, and classificatory (linear, quadratic, and the non-parametric k nearest neighbours). The philosophy of the package is described in Šlenker et al. 2022.


MorphoTools2

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The package MorphoTools2 is intended for multivariate analyses of morphological data. At the moment, various necessary tools are scattered across several R packages. This package wraps available statistical and graphical tools and provides a comprehensive framework for checking and manipulating input data, performing core statistical analyses and running a wide palette of functions designed to visualize results, making the workflow convenient and fast.

Installation

You can install the released version of MorphoTools2 from CRAN with:

install.packages("MorphoTools2")

And the development version from GitHub with:

# install.packages("devtools")
devtools::install_github("MarekSlenker/MorphoTools2")

Reference manual

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install.packages("MorphoTools2")

1.0.2.1 by Marek Šlenker, 2 years ago


https://github.com/MarekSlenker/MorphoTools2


Report a bug at https://github.com/MarekSlenker/MorphoTools2/issues


Browse source code at https://github.com/cran/MorphoTools2


Authors: Marek Šlenker [aut, cre] , Petr Koutecký [ctb] , Karol Marhold [ctb]


Documentation:   PDF Manual  


GPL-3 license


Imports ade4, candisc, car, class, ellipse, heplots, MASS, methods, plot3D, StatMatch, utils, vegan, stats

Suggests testthat, knitr, rmarkdown


See at CRAN