Package: HDElliptical
Type: Package
Title: High-Dimensional Methods for Elliptically Symmetric
        Distributions
Version: 0.1.3
Authors@R: c(
    person(
      given = "Long",
      family = "Feng",
      email = "flnankai@nankai.edu.cn",
      role = c("aut", "cre", "cph"),
      comment = "Copyright holder for the HDElliptical implementation"
    ),
    person(
      given = "Dan",
      family = "Zhuang",
      role = "ctb",
      comment = paste(
        "SEMC methodology and the external GEMcluster reference",
        "implementation used for validation; no GEMcluster source",
        "code is included"
      )
    )
  )
Description: 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>.
License: MIT + file LICENSE
URL: https://github.com/flnankai/HDElliptical
BugReports: https://github.com/flnankai/HDElliptical/issues
Depends: R (>= 4.2.0)
Imports: mvtnorm, Rcpp, stats
LinkingTo: Rcpp, RcppArmadillo
Suggests: knitr, rmarkdown, testthat (>= 3.0.0)
VignetteBuilder: knitr
Config/testthat/edition: 3
Encoding: UTF-8
NeedsCompilation: yes
SystemRequirements: C++17
RoxygenNote: 7.3.3
Packaged: 2026-10-14 11:37:37 UTC; root
Author: Long Feng [aut, cre, cph] (Copyright holder for the
        HDElliptical implementation), Dan Zhuang [ctb] (SEMC
        methodology and the external GEMcluster reference
        implementation used for validation; no GEMcluster source code
        is included)
Maintainer: Long Feng <flnankai@nankai.edu.cn>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-09-14 14:15:07 UTC
RemoteUrl: https://github.com/cran/HDElliptical
RemoteRef: HEAD
RemoteSha: 7fa5c2878b58d9ed5a63fe371366756306d0ffa7