https://github.com/sipemu/fdars
Functional Data Analysis in R and Rust - High-performance FDA algorithms including depth measures, metrics, clustering, smoothing, and regression
https://github.com/sipemu/fdars
data-science fda functional-data-analysis r rust statistics
Last synced: 29 days ago
JSON representation
Functional Data Analysis in R and Rust - High-performance FDA algorithms including depth measures, metrics, clustering, smoothing, and regression
- Host: GitHub
- URL: https://github.com/sipemu/fdars
- Owner: sipemu
- Created: 2025-12-12T13:28:10.000Z (2 months ago)
- Default Branch: main
- Last Pushed: 2026-01-03T21:34:02.000Z (about 1 month ago)
- Last Synced: 2026-01-05T00:16:54.269Z (about 1 month ago)
- Topics: data-science, fda, functional-data-analysis, r, rust, statistics
- Language: R
- Homepage: https://sipemu.github.io/fdars/
- Size: 145 MB
- Stars: 0
- Watchers: 0
- Forks: 0
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
# Functional Data Analysis (FDA)
[](https://github.com/sipemu/fdars/actions/workflows/r.yml)
[](https://github.com/sipemu/fdars/actions/workflows/rust-ci.yml)
[](https://crates.io/crates/fdars-core)
[](https://codecov.io/gh/sipemu/fdars)
[](https://opensource.org/licenses/MIT)
High-performance Functional Data Analysis tools implemented in Rust with R bindings.
## Packages
| Package | Language | Registry | Folder | Status |
|---------|----------|----------|--------|--------|
| fdars | R | CRAN | `fdars-r/` | [](https://CRAN.R-project.org/package=fdars) |
| fdars-core | Rust | crates.io | `fdars-core/` | [](https://crates.io/crates/fdars-core) |
## Features
- **Functional Data Operations**: Mean, centering, derivatives, Lp norms, geometric median
- **Depth Measures**: Fraiman-Muniz, modal, band, modified band, random projection, random Tukey, functional spatial, kernel functional spatial, modified epigraph index
- **Distance Metrics**: Lp distances, Hausdorff, DTW, Fourier-based semimetric, horizontal shift semimetric
- **Basis Representations**: B-splines, Fourier basis, P-splines with GCV/AIC/BIC selection
- **Clustering**: K-means, fuzzy c-means with silhouette and Calinski-Harabasz validation
- **Smoothing**: Nadaraya-Watson, local linear, local polynomial, k-NN
- **Regression**: Functional PCA, PLS, ridge regression
- **Outlier Detection**: LRT-based outlier detection with bootstrap thresholding
- **Seasonal Analysis**: Period estimation, peak detection, seasonal decomposition
## Installation
### R (fdars)
```r
# From GitHub (requires Rust toolchain)
devtools::install_github("sipemu/fdars", subdir = "fdars-r")
# From binary release (no Rust required)
# Download from GitHub Releases, then:
install.packages("path/to/fdars_x.y.z.tgz", repos = NULL, type = "mac.binary") # macOS
install.packages("path/to/fdars_x.y.z.zip", repos = NULL, type = "win.binary") # Windows
```
### Rust (fdars-core)
```toml
[dependencies]
fdars-core = "0.1"
```
## Documentation
- **R Package**: [https://sipemu.github.io/fdars/](https://sipemu.github.io/fdars/)
- **Rust Crate**: [https://docs.rs/fdars-core](https://docs.rs/fdars-core)
## License
MIT