Package: UNPaC
Title: Non-Parametric Cluster Significance Testing with Reference to a
        Unimodal Null Distribution
Version: 1.2.0
Authors@R: 
    c(person(given = c("Erika", "S."),
                        family = "Helgeson",
                        role = c("aut", "cre"),
                        email = "helge@umn.edu"),
                 person(given = "David",
                        family = "Vock",
                        role = "aut"),
                 person(given = "Eric",
                        family = "Bair",
                        role = "aut"))
Description: Assess the significance of identified clusters and
        estimates the true number of clusters by comparing the
        explained variation due to the clustering from the original
        data to that produced by clustering a unimodal reference
        distribution which preserves the covariance structure in the
        data. The reference distribution is generated using kernel
        density estimation and a Gaussian copula framework. A dimension
        reduction strategy and sparse covariance estimation optimize
        this method for the high-dimensional, low-sample size setting.
        This method is described in Helgeson, Vock, and Bair (2021)
        <doi:10.1111/biom.13376>.
License: MIT + file LICENSE
Encoding: UTF-8
RoxygenNote: 7.3.2
Imports: glasso, PDSCE
NeedsCompilation: no
Packaged: 2026-07-04 05:31:07 UTC; root
Author: Erika S. Helgeson [aut, cre], David Vock [aut], Eric Bair [aut]
Maintainer: Erika S. Helgeson <helge@umn.edu>
Repository: https://cran.r-universe.dev
Date/Publication: 2026-01-30 03:09:01 UTC
RemoteUrl: https://github.com/cran/UNPaC
RemoteRef: HEAD
RemoteSha: 7bd0bf57c4c22b9fea66aa7bce44199bad25fc1f