Package: RCTS
Title: Clustering Time Series While Resisting Outliers
Version: 0.2.4
Authors@R: 
    person(given = "Ewoud",
           family = "Heyndels",
           role = c("aut", "cre"),
           email = "ewoud.heyndels@vub.be",
           comment = c(ORCID = "0000-0003-4540-8571"))
Description: Robust Clustering of Time Series (RCTS) has the
        functionality to cluster time series using both the classical
        and the robust interactive fixed effects framework. The
        classical framework is developed in Ando & Bai (2017)
        <doi:10.1080/01621459.2016.1195743>. The implementation within
        this package excludes the SCAD-penalty on the estimations of
        beta. This robust framework is developed in Boudt & Heyndels
        (2022) <doi:10.1016/j.ecosta.2022.01.002> and is made robust
        against different kinds of outliers. The algorithm iteratively
        updates beta (the coefficients of the observable variables),
        group membership, and the latent factors (which can be common
        and/or group-specific) along with their loadings. The number of
        groups and factors can be estimated if they are unknown.
License: GPL (>= 2)
Encoding: UTF-8
LazyData: true
Roxygen: list(markdown = TRUE)
RoxygenNote: 7.2.3
Imports: stats, magrittr, dplyr, purrr, stringr, tidyr, tibble,
        ggplot2, ncvreg, robustbase, cellWise, rlang, Rdpack
Suggests: tsqn, doParallel, doSNOW, foreach, mclust, Matrix
RdMacros: Rdpack
Depends: R (>= 4.1.0)
Config/pak/sysreqs: libicu-dev
Repository: https://eh-in-r.r-universe.dev
Date/Publication: 2023-05-18 13:31:53 UTC
RemoteUrl: https://github.com/eh-in-r/rcts
RemoteRef: HEAD
RemoteSha: f6a1ba4cdddd14d5faae291c9e6120247752aac9
NeedsCompilation: no
Packaged: 2026-07-13 07:49:44 UTC; root
Author: Ewoud Heyndels [aut, cre] (ORCID:
    <https://orcid.org/0000-0003-4540-8571>)
Maintainer: Ewoud Heyndels <ewoud.heyndels@vub.be>