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TDAstats (version 0.4.1)

Pipeline for Topological Data Analysis

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. 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) .

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Install

install.packages('TDAstats')

Monthly Downloads

271

Version

0.4.1

License

GPL-3

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Maintainer

Raoul Wadhwa

Last Published

December 12th, 2019

Functions in TDAstats (0.4.1)

TDAstats

Statistical Inference for Persistent Homology in Topological Data Analysis
calculate_homology

Calculate Persistent Homology of a Point Cloud
unif3d

3-dimensional point cloud of a unit cube
plot_barcode

Plot Persistent Homology as Topological Barcode
plot_persist

Plot Persistent Homology as Persistence Diagram
unif2d

2-dimensional point cloud of a unit square
id_significant

Identify Significant Features in Persistent Homology
permutation_test

Statistical Inference for Topological Data Analysis
circle2d

2-dimensional point cloud of a unit circle
phom.dist

Calculate Distance between Homology Matrices
sphere3d

3-dimensional point cloud of a unit sphere