Topological data analysis studies structure and shape of the data using topological features. We provide a variety of algorithms to learn with persistent homology of the data based on functional summaries for clustering, hypothesis testing, visualization, and others. We refer to Wasserman (2018) <doi:10.1146/annurev-statistics-031017-100045> for a statistical perspective on the topic.
| Version: | 0.1.3 |
| Imports: | Rcpp, Rdpack, TDAstats, T4cluster, energy, ggplot2, maotai, stats, utils |
| LinkingTo: | Rcpp, RcppArmadillo |
| Published: | 2025-09-21 |
| DOI: | 10.32614/CRAN.package.TDAkit |
| Author: | Kisung You |
| Maintainer: | Kisung You <kisung.you at outlook.com> |
| License: | MIT + file LICENSE |
| NeedsCompilation: | yes |
| Materials: | NEWS |
| CRAN checks: | TDAkit results |
| Reference manual: | TDAkit.html , TDAkit.pdf |
| Package source: | TDAkit_0.1.3.tar.gz |
| Windows binaries: | r-devel: TDAkit_0.1.3.zip, r-release: TDAkit_0.1.3.zip, r-oldrel: TDAkit_0.1.3.zip |
| macOS binaries: | r-release (arm64): TDAkit_0.1.3.tgz, r-oldrel (arm64): TDAkit_0.1.3.tgz, r-release (x86_64): TDAkit_0.1.3.tgz, r-oldrel (x86_64): TDAkit_0.1.3.tgz |
| Old sources: | TDAkit archive |
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