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>.
| Version: | 0.4.1 |
| Depends: | R (≥ 3.3) |
| Imports: | ggplot2 (≥ 2.2.1),Rcpp (≥ 0.12.15) |
| LinkingTo: | Rcpp |
| Suggests: | testthat (≥ 2.0.0),knitr,rmarkdown,covr |
| Published: | 2019-12-12 |
| DOI: | 10.32614/CRAN.package.TDAstats |
| Author: | Raoul Wadhwa [aut, cre], Andrew Dhawan [aut], Drew Williamson [aut], Jacob Scott [aut], Jason Cory Brunson [ctb], Shota Ochi [ctb] |
| Maintainer: | Raoul Wadhwa <raoulwadhwa at gmail.com> |
| BugReports: | https://github.com/rrrlw/TDAstats/issues |
| License: | GPL-3 |
| URL: | https://github.com/rrrlw/TDAstats |
| NeedsCompilation: | yes |
| SystemRequirements: | C++11 |
| Citation: | TDAstats citation info |
| CRAN checks: | TDAstats results[issues need fixing before 2025-12-18] |
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