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
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)
NeedsCompilation: no
Packaged: 2023-05-18 14:05:51 UTC; hewoud
Author: Ewoud Heyndels [aut, cre] (<https://orcid.org/0000-0003-4540-8571>)
Maintainer: Ewoud Heyndels <ewoud.heyndels@vub.be>
Repository: CRAN
Date/Publication: 2023-05-18 14:30:02 UTC
Built: R 4.6.0; ; 2026-04-26 20:57:13 UTC; unix
