The R Journal: article published in 2016, volume 8:2

Escape from Boxland
Barret Schloerke, Hadley Wickham, Dianne Cook and Heike Hofmann , The R Journal (2016) 8:2, pages 243-257.

Abstract A library of common geometric shapes can be used to train our brains for understanding data structure in high-dimensional Euclidean space. This article describes the methods for producing cubes, spheres, simplexes, and tori in multiple dimensions. It also describes new ways to define and generate high-dimensional tori. The algorithms are described, critical code chunks are given, and a large collection of generated data are provided. These are available in the R package geozoo, and selected movies and images, are available on the GeoZoo web site (http://schloerke.github.io/geozoo/).

Received: 2016-03-10; online 2016-11-21
CRAN packages: geozoo, tourr, bitops, geozoo, geozoo
CRAN Task Views implied by cited CRAN packages: Multivariate

This article is licensed under a Creative Commons Attribution 3.0 Unported license .

@article{RJ-2016-044,
  author = {Barret Schloerke and Hadley Wickham and Dianne Cook and
          Heike Hofmann},
  title = {{Escape from Boxland}},
  year = {2016},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2016-044},
  url = {https://doi.org/10.32614/RJ-2016-044},
  pages = {243--257},
  volume = {8},
  number = {2}
}