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 < https://github.com/Ripser/ripser>. This package has been published as Wadhwa et al. (2018) .


News

Reference manual

It appears you don't have a PDF plugin for this browser. You can click here to download the reference manual.

install.packages("TDAstats")

0.4.0 by Raoul Wadhwa, 7 months ago


https://github.com/rrrlw/TDAstats


Report a bug at https://github.com/rrrlw/TDAstats/issues


Browse source code at https://github.com/cran/TDAstats


Authors: Raoul Wadhwa [aut, cre] , Andrew Dhawan [aut] , Drew Williamson [aut] , Jacob Scott [aut]


Documentation:   PDF Manual  


GPL-3 license


Imports ggplot2, Rcpp

Suggests testthat, knitr, rmarkdown, covr

Linking to Rcpp

System requirements: C++11


See at CRAN