a persistence diagram. There are five goals of this package: (1) convert persistence diagrams
for pairs of persistence diagrams, (3) provide methods for machine learning
and inference for persistence diagrams which scale well, (4) deliver a fast implementation
of persistent homology via a python interface, and (5) contribute tools for the interpretation of
Suggests: rmarkdown, knitr, testthat (>= 3.0.0), TDA, TDAstats,
Packaged: 2022-11-08 16:23:13 UTC; jibaccount

Title: Pipeline for Topological Data Analysis
person("Andrew", "Dhawan", role = "aut"),
person("Drew", "Williamson", role = "aut"),
Description: 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.
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,
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>.

Suggests: testthat (>= 2.0.0), knitr, rmarkdown

The published form of TDAstats can be found in Wadhwa et al. (2018)
This package has been published as Wadhwa et al. (2018)
Suggests: testthat (>= 2.0.0), knitr, rmarkdown, covr

person("Jason Cory", "Brunson", role = "ctb"),

Title: Vector Summaries of Persistence Diagrams
person("Umar","Islambekov", email = "iumar@bgsu.edu", role=c("aut")),
person("Alexey", "Luchinsky", email = "aluchi@bgsu.edu", role = c("aut", "cre")),
person("Hasani", "Pathirana", email = "pathirh@bgsu.edu", role = "ctb")
Description: Tools for computing various vector summaries of persistence diagrams
studied in Topological Data Analysis. For improved computational efficiency,
all code for the vector summaries is written in 'C++' using the 'Rcpp' package.
Imports: Rcpp (>= 1.0.9), TDA, microbenchmark
Packaged: 2022-08-18 19:53:08 UTC; luchinsky