https://github.com/egarpor/polykde
Kernel density estimation on the polysphere, hypersphere, and circle. Includes functions for density estimation, regression estimation, ridge estimation, bandwidth selection, kernels, samplers, and homogeneity tests
https://github.com/egarpor/polykde
circular-statistics directional-statistics kernel-smoothing r
Last synced: 7 months ago
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Kernel density estimation on the polysphere, hypersphere, and circle. Includes functions for density estimation, regression estimation, ridge estimation, bandwidth selection, kernels, samplers, and homogeneity tests
- Host: GitHub
- URL: https://github.com/egarpor/polykde
- Owner: egarpor
- License: gpl-3.0
- Created: 2025-02-07T08:28:27.000Z (over 1 year ago)
- Default Branch: main
- Last Pushed: 2025-02-11T23:58:05.000Z (over 1 year ago)
- Last Synced: 2025-02-12T00:29:24.491Z (over 1 year ago)
- Topics: circular-statistics, directional-statistics, kernel-smoothing, r
- Language: R
- Homepage:
- Size: 389 KB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.Rmd
- Changelog: NEWS.md
- License: LICENSE.md
Awesome Lists containing this project
README
---
output:
md_document:
variant: gfm
---
```{r, echo = FALSE}
knitr::opts_chunk$set(
collapse = TRUE, comment = "#>", fig.path = "README/README-",
message = FALSE, warning = FALSE, fig.asp = 1, fig.align = 'center'
)
```
polykde
=======
```{r, badges, echo = FALSE, results = 'asis'}
cat(
badger::badge_license(license = "GPLv3", color = "blue",
url = "https://www.gnu.org/licenses/gpl-3.0"),
badger::badge_github_actions(action = "R-CMD-check"),
badger::badge_github_actions(action = "test-coverage"),
badger::badge_codecov(),
badger::badge_cran_release(color = "green"),
badger::badge_cran_download(pkg = NULL, type = "grand-total"),
badger::badge_cran_download(pkg = NULL, type = "last-month")
)
```
## Overview
Companion package for the article *Kernel density estimation with polyspherical data and its applications* (García-Portugués and Meilán-Vila, 2024).
## Replicability
The folder `/replication` contains the scripts to replicate the numerical experiments of the Supplementary Material (SM):
* The script `kde-sims.R` reproduces the asymptotic normality experiment in Section B.1 of the SM.
* The script `kde-efic.R` computes the kernel efficiency table in Section B.2 of the SM and plots in Section 4 of the paper.
* The two scripts `jsd-sims-k2-S2.R` and `jsd-sims-k3-S10^2.R` reproduce two simulation experiments for the $k$-sample test in Section B.3 of the SM.
## References
García-Portugués, E. and Meilán-Vila, A. (2024). Kernel density estimation with polyspherical data and its applications. *arXiv:2411.04166*. [doi:10.48550/arXiv.2411.04166](https://doi.org/10.48550/arXiv.2411.04166).
García-Portugués, E. and Meilán-Vila, A. (2023). Hippocampus shape analysis via skeletal models and kernel smoothing. In Larriba, Y. (Ed.), *Statistical Methods at the Forefront of Biomedical Advances*, pp. 63--82. Springer, Cham. [doi:10.1007/978-3-031-32729-2_4](https://doi.org/10.1007/978-3-031-32729-2_4).