HDiR: An R Package for Computation and Nonparametric Plug-in Estimation of Directional Highest Density Regions and General Level Sets

A deeper understanding of a distribution support, being able to determine regions of a certain (possibly high) probability content is an important task in several research fields. Package HDiR for R is designed for exact computation of directional (circular and spherical) highest density regions and density level sets when the density is fully known. Otherwise, HDiR implements nonparametric plug-in methods based on different kernel density estimates for reconstructing this kind of sets. Additionally, it also allows the computation and plug-in estimation of level sets for general functions (not necessarily a density). Some exploratory tools, such as suitably adapted distances and scatterplots, are also implemented. Two original datasets and spherical density models are used for illustrating HDiR functionalities.

Paula Saavedra-Nieves (CITMAga, Galician Centre for Mathematical Research and Technology) , Rosa M. Crujeiras (CITMAga, Galician Centre for Mathematical Research and Technology)
2022-12-20

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Supplementary materials are available in addition to this article. It can be downloaded at RJ-2022-046.zip

References

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Citation

For attribution, please cite this work as

Saavedra-Nieves & Crujeiras, "The R Journal: HDiR: An R Package for Computation and Nonparametric Plug-in Estimation of Directional Highest Density Regions and General Level Sets", The R Journal, 2022

BibTeX citation

@article{RJ-2022-046,
  author = {Saavedra-Nieves, Paula and Crujeiras, Rosa M.},
  title = {The R Journal: HDiR: An R Package for Computation and Nonparametric Plug-in Estimation of Directional Highest Density Regions and General Level Sets},
  journal = {The R Journal},
  year = {2022},
  note = {https://doi.org/10.32614/RJ-2022-046},
  doi = {10.32614/RJ-2022-046},
  volume = {14},
  issue = {3},
  issn = {2073-4859},
  pages = {121-141}
}