Packaged: 2020-06-03 10:55:55 UTC; TGuillerme

Packaged: 2020-09-04 10:13:10 UTC; TGuillerme

grDevices, methods, mnormt, parallel, phangorn, phyclust,
Packaged: 2020-09-25 16:46:38 UTC; TGuillerme

Packaged: 2021-04-17 13:43:24 UTC; TGuillerme

Packaged: 2022-01-24 16:33:32 UTC; tguillerme

Imports: ade4, castor, Claddis, geometry, geoscale, graphics,
grDevices, MASS, methods, mnormt, parallel, phangorn, phyclust,
Packaged: 2022-04-26 15:10:30 UTC; tguillerme

Description: A modular package for measuring disparity (multidimensional space occupancy). Disparity can be calculated from any matrix defining a multidimensional space. The package provides a set of implemented metrics to measure properties of the space and allows users to provide and test their own metrics. The package also provides functions for looking at disparity in a serial way (e.g. disparity through time) or per groups as well as visualising the results. Finally, this package provides several statistical tests for disparity analysis.
Imports: ade4, castor, Claddis, ellipse, geometry, graphics, grDevices,
MASS, methods, mnormt, parallel, phangorn, phyclust, utils,
Suggests: MCMCglmm, geoscale, testthat, knitr
Packaged: 2022-08-08 17:10:54 UTC; tguillerme

Title: Disparity Filter Algorithm of Weighted Network
Description: Disparity filter is a network reduction algorithm to extract the backbone structure of both directed and undirected weighted networks. Disparity filter can reduce the network without destroying the multi-scale nature of the network. The algorithm has been developed by M. Angeles Serrano, Marian Boguna, and Alessandro Vespignani in Extracting the multiscale backbone of complex weighted networks, Proceedings of the national academy of sciences 106 (16).

Title: Disparity Filter Algorithm for Weighted Networks
person("Alessandro", "Bessi", email = "alessandro.bessi@iusspavia.it", role = c("aut", "cre")),
person("Francois", "Briatte", email = "f.briatte@gmail.com", role = "aut"))
Description: The disparity filter algorithm is a network reduction technique to
identify the 'backbone' structure of a weighted network without destroying
its multi-scale nature. The algorithm is documented in M. Angeles Serrano,
Marian Boguna and Alessandro Vespignani in "Extracting the multiscale
backbone of complex weighted networks", Proceedings of the National Academy
of Sciences 106 (16), 2009. This implementation of the algorithm supports