spherepc: An R Package for Dimension Reduction on a Sphere

Dimension reduction is a technique that can compress given data and reduce noise. Recently, a dimension reduction technique on spheres, called spherical principal curves (SPC), has been proposed. SPC fits a curve that passes through the middle of data with a stationary property on spheres. In addition, a study of local principal geodesics (LPG) is considered to identify the complex structure of data. Through the description and implementation of various examples, this paper introduces an R package spherepc for dimension reduction of data lying on a sphere, including existing methods, SPC and LPG.

Jongmin Lee (Department of Statistics) , Jang-Hyun Kim (Department of Computer Science and Engineering) , Hee-Seok Oh (Department of Statistics)
2022-06-21

Supplementary materials

Supplementary materials are available in addition to this article. It can be downloaded at RJ-2022-016.zip

References

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Citation

For attribution, please cite this work as

Lee, et al., "spherepc: An R Package for Dimension Reduction on a Sphere", The R Journal, 2022

BibTeX citation

@article{RJ-2022-016,
  author = {Lee, Jongmin and Kim, Jang-Hyun and Oh, Hee-Seok},
  title = {spherepc: An R Package for Dimension Reduction on a Sphere},
  journal = {The R Journal},
  year = {2022},
  note = {https://doi.org/10.32614/RJ-2022-016},
  doi = {10.32614/RJ-2022-016},
  volume = {14},
  issue = {1},
  issn = {2073-4859},
  pages = {167-181}
}