TDAstats (0.4.1)

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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) . For a general background on computing persistent homology for topological data analysis, see Otter et al. (2017) . To learn more about how the permutation test is used for nonparametric statistical inference in topological data analysis, read Robinson & Turner (2017) . 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) .

Maintainer: Raoul Wadhwa
Author(s): Raoul Wadhwa [aut, cre], Andrew Dhawan [aut], Drew Williamson [aut], Jacob Scott [aut], Jason Cory Brunson [ctb], Shota Ochi [ctb]

License: GPL-3

Uses: ggplot2, Rcpp, testthat, knitr, rmarkdown, covr

Released 6 months ago.

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