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 <>. 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], Jason Cory Brunson [ctb], Shota Ochi [ctb]
MaintainerRaoul Wadhwa <>
Package repositoryView on CRAN
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TDAstats documentation built on Dec. 16, 2019, 1:36 a.m.