HDElliptical
High-Dimensional Methods for Elliptically Symmetric Distributions
Fast, documented implementations of robust estimation, testing, dimension reduction, classification, and clustering methods for high-dimensional elliptically symmetric data. Computational kernels use 'Rcpp' and 'RcppArmadillo'. The package follows methods reviewed in Feng (2026), "High-Dimensional Data Analysis for Elliptically Symmetric Distributions" <https://github.com/flnankai/HDElliptical/releases>.
README
# Deterministic benchmarks Run the installed-package benchmark with: ```sh Rscript run-benchmarks.R HDElliptical-benchmarks.csv 5 1 0.05 ``` The harness times one representative callable workflow per book chapter and records a deterministic numeric fingerprint. It uses no package beyond HDElliptical itself. The timings are descriptive machine-local evidence, not a paper-specific simulation, size/power experiment, or performance guarantee. Arguments are the output CSV, the number of measured repetitions, and the number of warm-up calls, followed by the minimum elapsed time used to calibrate each measurement batch. The defaults are 5, 1, and 0.05 seconds. The script reports per-call timings together with the number of calls in each batch, avoiding zero-resolution timings for fast methods. It fails if repeated calls produce different numeric fingerprints.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.2 |
rolling linux/jammy R-4.5 | HDElliptical_0.1.2.tar.gz |
3.8 MiB |
0.1.2 |
rolling linux/noble R-4.5 | HDElliptical_0.1.2.tar.gz |
3.9 MiB |
0.1.2 |
rolling source/ R- | HDElliptical_0.1.2.tar.gz |
983.5 KiB |
0.1.2 |
latest linux/jammy R-4.5 | HDElliptical_0.1.2.tar.gz |
3.8 MiB |
0.1.2 |
latest linux/noble R-4.5 | HDElliptical_0.1.2.tar.gz |
3.9 MiB |
0.1.2 |
latest source/ R- | HDElliptical_0.1.2.tar.gz |
983.5 KiB |
0.1.2 |
2026-04-23 source/ R- | HDElliptical_0.1.2.tar.gz |
0 B |