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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
Citation | TDAstats citation info |
github.com/rrrlw/TDAstats | |
System requirements | C++11 |
Bug report | File report |
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