tdaunif: Uniform Manifold Samplers for Topological Data Analysis

Uniform random samples from simple manifolds, sometimes with noise, are commonly used to test topological data analytic (TDA) tools. This package includes samplers powered by two techniques: analytic volume-preserving parameterizations, as employed by Arvo (1995) <doi:10.1145/218380.218500>, and rejection sampling, as employed by Diaconis, Holmes, and Shahshahani (2013) <doi:10.1214/12-IMSCOLL1006>.

Version: 0.1.0
Depends: R (≥ 3.3.0)
Suggests: knitr, rmarkdown, testthat, vdiffr (≥ 0.2)
Published: 2020-10-26
Author: Jason Cory Brunson [aut, cre], Brandon Demkowicz [aut], Sanmati Choudhary [aut]
Maintainer: Jason Cory Brunson <cornelioid at gmail.com>
BugReports: https://github.com/corybrunson/tdaunif/issues
License: GPL-3
URL: https://corybrunson.github.io/tdaunif/
NeedsCompilation: no
Materials: README NEWS
CRAN checks: tdaunif results

Downloads:

Reference manual: tdaunif.pdf
Vignettes: uniform and stratified sampling from manifolds
Package source: tdaunif_0.1.0.tar.gz
Windows binaries: r-devel: tdaunif_0.1.0.zip, r-release: tdaunif_0.1.0.zip, r-oldrel: tdaunif_0.1.0.zip
macOS binaries: r-release: tdaunif_0.1.0.tgz, r-oldrel: tdaunif_0.1.0.tgz

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