TDAstats: Pipeline for Topological Data Analysis

A comprehensive toolset for any useR conducting topological data analysis, specifically via the calculation of persistent homology in a Vietoris-Rips complex. The tools this package currently provides can be conveniently split into three main sections: (1) calculating persistent homology; (2) conducting statistical inference on persistent homology calculations; (3) visualizing persistent homology and statistical inference. The published form of TDAstats can be found in Wadhwa et al. (2018) <doi:10.21105/joss.00860>. For a general background on computing persistent homology for topological data analysis, see Otter et al. (2017) <doi:10.1140/epjds/s13688-017-0109-5>. To learn more about how the permutation test is used for nonparametric statistical inference in topological data analysis, read Robinson & Turner (2017) <doi:10.1007/s41468-017-0008-7>. To learn more about how TDAstats calculates persistent homology, you can visit the GitHub repository for Ripser, the software that works behind the scenes at <https://github.com/Ripser/ripser>. This package has been published as Wadhwa et al. (2018) <doi:10.21105/joss.00860>.

Package details

AuthorRaoul Wadhwa [aut, cre], Andrew Dhawan [aut], Drew Williamson [aut], Jacob Scott [aut]
MaintainerRaoul Wadhwa <[email protected]>
LicenseGPL-3
Version0.4.0
URL https://github.com/rrrlw/TDAstats
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("TDAstats")

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TDAstats documentation built on May 1, 2019, 10:21 p.m.